Search Results for author: Jun Li

Found 197 papers, 43 papers with code

Federated Learning in Intelligent Transportation Systems: Recent Applications and Open Problems

no code implementations20 Sep 2023 Shiying Zhang, Jun Li, Long Shi, Ming Ding, Dinh C. Nguyen, Wuzheng Tan, Jian Weng, Zhu Han

Intelligent transportation systems (ITSs) have been fueled by the rapid development of communication technologies, sensor technologies, and the Internet of Things (IoT).

Federated Learning Object Recognition

TSSAT: Two-Stage Statistics-Aware Transformation for Artistic Style Transfer

no code implementations12 Sep 2023 Haibo Chen, Lei Zhao, Jun Li, Jian Yang

To address this issue, we imitate the drawing process of humans and propose a Two-Stage Statistics-Aware Transformation (TSSAT) module, which first builds the global style foundation by aligning the global statistics of content and style features and then further enriches local style details by swapping the local statistics (instead of local features) in a patch-wise manner, significantly improving the stylization effects.

Style Transfer

A physics-informed and attention-based graph learning approach for regional electric vehicle charging demand prediction

no code implementations11 Sep 2023 Haohao Qu, Haoxuan Kuang, Jun Li, Linlin You

Along with the proliferation of electric vehicles (EVs), optimizing the use of EV charging space can significantly alleviate the growing load on intelligent transportation systems.

Graph Learning Meta-Learning +1

Create Your World: Lifelong Text-to-Image Diffusion

no code implementations8 Sep 2023 Gan Sun, Wenqi Liang, Jiahua Dong, Jun Li, Zhengming Ding, Yang Cong

Text-to-image generative models can produce diverse high-quality images of concepts with a text prompt, which have demonstrated excellent ability in image generation, image translation, etc.

Image Generation

DMKD: Improving Feature-based Knowledge Distillation for Object Detection Via Dual Masking Augmentation

no code implementations6 Sep 2023 Guang Yang, Yin Tang, Zhijian Wu, Jun Li, Jianhua Xu, Xili Wan

Recent mainstream masked distillation methods function by reconstructing selectively masked areas of a student network from the feature map of its teacher counterpart.

Knowledge Distillation object-detection +1

RigNet++: Efficient Repetitive Image Guided Network for Depth Completion

no code implementations1 Sep 2023 Zhiqiang Yan, Xiang Li, Zhenyu Zhang, Jun Li, Jian Yang

In the latter branch, we introduce a repetitive guidance module based on dynamic convolution, in which an efficient convolution factorization is proposed to reduce the complexity while modeling high-frequency structures progressively.

Depth Completion Depth Estimation +1

Fragment and Integrate Network (FIN): A Novel Spatial-Temporal Modeling Based on Long Sequential Behavior for Online Food Ordering Click-Through Rate Prediction

no code implementations30 Aug 2023 Jun Li, Jingjian Wang, Hongwei Wang, Xing Deng, Jielong Chen, Bing Cao, Zekun Wang, Guanjie Xu, Ge Zhang, Feng Shi, Hualei Liu

(ii) Integrate Network (IN) builds a new integrated sequence by utilizing spatial-temporal interaction on MSS and captures the comprehensive spatial-temporal representation by modeling the integrated sequence with a complicated attention.

Click-Through Rate Prediction Recommendation Systems

SkipcrossNets: Adaptive Skip-cross Fusion for Road Detection

no code implementations24 Aug 2023 Xinyu Zhang, Yan Gong, Zhiwei Li, Xin Gao, Dafeng Jin, Jun Li, Huaping Liu

Multi-modal fusion is increasingly being used for autonomous driving tasks, as images from different modalities provide unique information for feature extraction.

Autonomous Driving

Dynamic Dual-Graph Fusion Convolutional Network For Alzheimer's Disease Diagnosis

no code implementations5 Aug 2023 Fanshi Li, Zhihui Wang, Yifan Guo, Congcong Liu, Yanjie Zhu, Yihang Zhou, Jun Li, Dong Liang, Haifeng Wang

In this paper, a dynamic dual-graph fusion convolutional network is proposed to improve Alzheimer's disease (AD) diagnosis performance.

Graph Learning

Analysis and Optimization of Wireless Federated Learning with Data Heterogeneity

no code implementations4 Aug 2023 Xuefeng Han, Jun Li, Wen Chen, Zhen Mei, Kang Wei, Ming Ding, H. Vincent Poor

With the rapid proliferation of smart mobile devices, federated learning (FL) has been widely considered for application in wireless networks for distributed model training.

Federated Learning Scheduling

Aspect based sentimental analysis for travellers' reviews

no code implementations1 Aug 2023 Mohammed Saad M Alaydaa, Jun Li, Karl Jinkins

The results provide tangible reasons to use aspect based sentimental analysis in order to understand more the travellers and spot airport services that are in need for improvement.

Management TAG

UniAP: Unifying Inter- and Intra-Layer Automatic Parallelism by Mixed Integer Quadratic Programming

no code implementations31 Jul 2023 Hao Lin, Ke wu, Jun Li, Wu-Jun Li

To the best of our knowledge, UniAP is the first work to unify these two categories to search for a globally optimal strategy.

Creative Birds: Self-Supervised Single-View 3D Style Transfer

2 code implementations26 Jul 2023 Renke Wang, Guimin Que, Shuo Chen, Xiang Li, Jun Li, Jian Yang

Our focus lies primarily on birds, a popular subject in 3D reconstruction, for which no existing single-view 3D transfer methods have been developed. The method we propose seeks to generate a 3D mesh shape and texture of a bird from two single-view images.

3D Reconstruction Style Transfer

Bayesian Linear Regression with Cauchy Prior and Its Application in Sparse MIMO Radar

no code implementations20 Jul 2023 Jun Li, Ryan Wu, I-Tai Lu, Dongyin Ren

In this paper, a sparse signal recovery algorithm using Bayesian linear regression with Cauchy prior (BLRC) is proposed.


General vs. Long-Tailed Age Estimation: An Approach to Kill Two Birds with One Stone

no code implementations19 Jul 2023 Zenghao Bao, Zichang Tan, Jun Li, Jun Wan, Xibo Ma, Zhen Lei

Driven by this, some works suggest that each class should be treated equally to improve performance in tail classes (with a minority of samples), which can be summarized as Long-tailed Age Estimation.

Age Estimation MORPH

Mobility-Aware Joint User Scheduling and Resource Allocation for Low Latency Federated Learning

no code implementations18 Jul 2023 Kecheng Fan, Wen Chen, Jun Li, Xiumei Deng, Xuefeng Han, Ming Ding

As an efficient distributed machine learning approach, Federated learning (FL) can obtain a shared model by iterative local model training at the user side and global model aggregating at the central server side, thereby protecting privacy of users.

Federated Learning Scheduling

NCL++: Nested Collaborative Learning for Long-Tailed Visual Recognition

no code implementations29 Jun 2023 Zichang Tan, Jun Li, Jinhao Du, Jun Wan, Zhen Lei, Guodong Guo

To achieve the collaborative learning in long-tailed learning, the balanced online distillation is proposed to force the consistent predictions among different experts and augmented copies, which reduces the learning uncertainties.

Learnable Differencing Center for Nighttime Depth Perception

1 code implementation26 Jun 2023 Zhiqiang Yan, Yupeng Zheng, Chongyi Li, Jun Li, Jian Yang

Depth completion is the task of recovering dense depth maps from sparse ones, usually with the help of color images.

Depth Completion Depth Estimation

Variable Radiance Field for Real-Life Category-Specifc Reconstruction from Single Image

no code implementations8 Jun 2023 Kun Wang, Zhiqiang Yan, Zhenyu Zhang, Xiang Li, Jun Li, Jian Yang

Our key contributions are: (1) We parameterize the geometry and appearance of the object using a multi-scale global feature extractor, which avoids frequent point-wise feature retrieval and camera dependency.

Contrastive Learning Retrieval

EfficientSRFace: An Efficient Network with Super-Resolution Enhancement for Accurate Face Detection

no code implementations4 Jun 2023 Guangtao Wang, Jun Li, Jie Xie, Jianhua Xu, Bo Yang

In face detection, low-resolution faces, such as numerous small faces of a human group in a crowded scene, are common in dense face prediction tasks.

Benchmarking Face Detection +1

Self-Aware Trajectory Prediction for Safe Autonomous Driving

no code implementations16 May 2023 Wenbo Shao, Jun Li, Hong Wang

Trajectory prediction is one of the key components of the autonomous driving software stack.

Autonomous Driving Trajectory Prediction

Path Planning for Air-Ground Robot Considering Modal Switching Point Optimization

no code implementations14 May 2023 Xiaoyu Wang, Kangyao Huang, Xinyu Zhang, Honglin Sun, Wenzhuo LIU, Huaping Liu, Jun Li, Pingping Lu

A robot for the field application environment was proposed, and a lightweight global spatial planning technique for the robot based on the graph-search algorithm taking mode switching point optimization into account, with an emphasis on energy efficiency, searching speed, and the viability of real deployment.

Human Machine Co-adaption Interface via Cooperation Markov Decision Process System

no code implementations3 May 2023 Kairui Guo, Adrian Cheng, Yaqi Li, Jun Li, Rob Duffield, Steven W. Su

Based on the proposed co-adaptive MDPs, the simulation study indicates the non-stationary problem can be mitigated using various proposed Policy Improvement approaches.

Model-based Reinforcement Learning Multi-agent Reinforcement Learning +1

ScatterFormer: Locally-Invariant Scattering Transformer for Patient-Independent Multispectral Detection of Epileptiform Discharges

1 code implementation26 Apr 2023 Ruizhe Zheng, Jun Li, Yi Wang, Tian Luo, Yuguo Yu

Patient-independent detection of epileptic activities based on visual spectral representation of continuous EEG (cEEG) has been widely used for diagnosing epilepsy.

EEG Seizure Detection

Informative Data Selection with Uncertainty for Multi-modal Object Detection

no code implementations23 Apr 2023 Xinyu Zhang, Zhiwei Li, Zhenhong Zou, Xin Gao, Yijin Xiong, Dafeng Jin, Jun Li, Huaping Liu

To quantify the correlation in multi-modal information, we model the uncertainty, as the inverse of data information, in different modalities and embed it in the bounding box generation.

2D Object Detection Informativeness +2

Gradient Sparsification for Efficient Wireless Federated Learning with Differential Privacy

no code implementations9 Apr 2023 Kang Wei, Jun Li, Chuan Ma, Ming Ding, Feng Shu, Haitao Zhao, Wen Chen, Hongbo Zhu

Specifically, we first design a random sparsification algorithm to retain a fraction of the gradient elements in each client's local training, thereby mitigating the performance degradation induced by DP and and reducing the number of transmission parameters over wireless channels.

Federated Learning Scheduling +1

Design of Two-Level Incentive Mechanisms for Hierarchical Federated Learning

no code implementations9 Apr 2023 Shunfeng Chu, Jun Li, Kang Wei, Yuwen Qian, Kunlun Wang, Feng Shu, Wen Chen

In this paper, we design two-level incentive mechanisms for the HFL with a two-tiered computing structure to encourage the participation of entities in each tier in the HFL training.

Federated Learning Vocal Bursts Valence Prediction

LogoNet: a fine-grained network for instance-level logo sketch retrieval

1 code implementation5 Apr 2023 Binbin Feng, Jun Li, Jianhua Xu

To our knowledge, this is the first publicly available instance-level logo sketch dataset.

Benchmarking Retrieval +1

Boundary-to-Solution Mapping for Groundwater Flows in a Toth Basin

no code implementations28 Mar 2023 Jingwei Sun, Jun Li, Yonghong Hao, Cuiting Qi, Chunmei Ma, Huazhi Sun, Negash Begashaw, Gurcan Comet, Yi Sun, Qi Wang

In this paper, the authors propose a new approach to solving the groundwater flow equation in the Toth basin of arbitrary top and bottom topographies using deep learning.

Pi-ViMo: Physiology-inspired Robust Vital Sign Monitoring using mmWave Radars

no code implementations24 Mar 2023 Bo Zhang, Boyu Jiang, Rong Zheng, XiaoPing Zhang, Jun Li, Qiang Xu

In this paper, we address these limitations and present "Pi-ViMo", a non-contact Physiology-inspired Robust Vital Sign Monitoring system, using mmWave radars.

Template Matching

Frozen Language Model Helps ECG Zero-Shot Learning

no code implementations22 Mar 2023 Jun Li, Che Liu, Sibo Cheng, Rossella Arcucci, Shenda Hong

In downstream classification tasks, METS achieves around 10% improvement in performance without using any annotated data via zero-shot classification, compared to other supervised and SSL baselines that rely on annotated data.

Language Modelling Self-Supervised Learning +1

BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection

1 code implementation CVPR 2023 Lei Yang, Kaicheng Yu, Tao Tang, Jun Li, Kun Yuan, Li Wang, Xinyu Zhang, Peng Chen

In essence, instead of predicting the pixel-wise depth, we regress the height to the ground to achieve a distance-agnostic formulation to ease the optimization process of camera-only perception methods.

3D Object Detection Autonomous Driving +1

O2CTA: Introducing Annotations from OCT to CCTA in Coronary Plaque Analysis

no code implementations11 Mar 2023 Jun Li, Kexin Li, Yafeng Zhou, S. Kevin Zhou

Therefore, it is clinically critical to introduce annotations of plaque tissue and lumen characteristics from OCT to paired CCTA scans, denoted as \textbf{the O2CTA problem} in this paper.

Non-aligned supervision for Real Image Dehazing

no code implementations8 Mar 2023 Junkai Fan, Fei Guo, Jianjun Qian, Xiang Li, Jun Li, Jian Yang

In particular, we explore a non-alignment setting by utilizing a clear reference image that is not aligned with the hazy input image to supervise the dehazing network through a multi-scale reference loss that compares the features of the two images.

Image Dehazing

Amplitude-Varying Perturbation for Balancing Privacy and Utility in Federated Learning

no code implementations7 Mar 2023 Xin Yuan, Wei Ni, Ming Ding, Kang Wei, Jun Li, H. Vincent Poor

The contribution of the new DP mechanism to the convergence and accuracy of privacy-preserving FL is corroborated, compared to the state-of-the-art Gaussian noise mechanism with a persistent noise amplitude.

Federated Learning Privacy Preserving

EfficientFace: An Efficient Deep Network with Feature Enhancement for Accurate Face Detection

no code implementations23 Feb 2023 Guangtao Wang, Jun Li, Zhijian Wu, Jianhua Xu, Jifeng Shen, Wankou Yang

Besides, this is conducive to estimating the locations of faces and enhancing the descriptive power of face features.

Descriptive Face Detection

InOR-Net: Incremental 3D Object Recognition Network for Point Cloud Representation

no code implementations20 Feb 2023 Jiahua Dong, Yang Cong, Gan Sun, Lixu Wang, Lingjuan Lyu, Jun Li, Ender Konukoglu

Moreover, they cannot explore which 3D geometric characteristics are essential to alleviate the catastrophic forgetting on old classes of 3D objects.

3D Object Recognition Fairness

Structure Flow-Guided Network for Real Depth Super-Resolution

no code implementations31 Jan 2023 Jiayi Yuan, Haobo Jiang, Xiang Li, Jianjun Qian, Jun Li, Jian Yang

Specifically, our framework consists of a cross-modality flow-guided upsampling network (CFUNet) and a flow-enhanced pyramid edge attention network (PEANet).

Depth Estimation Depth Prediction +1

Recurrent Structure Attention Guidance for Depth Super-Resolution

no code implementations31 Jan 2023 Jiayi Yuan, Haobo Jiang, Xiang Li, Jianjun Qian, Jun Li, Jian Yang

Second, instead of the coarse concatenation guidance, we propose a recurrent structure attention block, which iteratively utilizes the latest depth estimation and the image features to jointly select clear patterns and boundaries, aiming at providing refined guidance for accurate depth recovery.

Depth Estimation Super-Resolution

AMD: Adaptive Masked Distillation for Object Detection

no code implementations31 Jan 2023 Guang Yang, Yin Tang, Jun Li, Jianhua Xu, Xili Wan

As a general model compression paradigm, feature-based knowledge distillation allows the student model to learn expressive features from the teacher counterpart.

Knowledge Distillation Model Compression +2

Privacy-Preserving Joint Edge Association and Power Optimization for the Internet of Vehicles via Federated Multi-Agent Reinforcement Learning

no code implementations26 Jan 2023 Yan Lin, Jinming Bao, Yijin Zhang, Jun Li, Feng Shu, Lajos Hanzo

Proactive edge association is capable of improving wireless connectivity at the cost of increased handover (HO) frequency and energy consumption, while relying on a large amount of private information sharing required for decision making.

Decision Making Multi-agent Reinforcement Learning +1

How Does Traffic Environment Quantitatively Affect the Autonomous Driving Prediction?

no code implementations11 Jan 2023 Wenbo Shao, Yanchao Xu, Jun Li, Chen Lv, Weida Wang, Hong Wang

The results indicate that the deep ensemble-based method has advantages in improving prediction robustness and estimating epistemic uncertainty.

Autonomous Driving Decision Making +1

SS-CPGAN: Self-Supervised Cut-and-Pasting Generative Adversarial Network for Object Segmentation

no code implementations1 Jan 2023 Kunal Chaturvedi, Ali Braytee, Jun Li, Mukesh Prasad

This paper proposes a novel self-supervised based Cut-and-Paste GAN to perform foreground object segmentation and generate realistic composite images without manual annotations.

Semantic Segmentation

Reversible Column Networks

1 code implementation22 Dec 2022 Yuxuan Cai, Yizhuang Zhou, Qi Han, Jianjian Sun, Xiangwen Kong, Jun Li, Xiangyu Zhang

Such architectural scheme attributes RevCol very different behavior from conventional networks: during forward propagation, features in RevCol are learned to be gradually disentangled when passing through each column, whose total information is maintained rather than compressed or discarded as other network does.

Image Classification object-detection +2

Robust Sum-Rate Maximization in Transmissive RMS Transceiver-Enabled SWIPT Networks

no code implementations10 Dec 2022 Zhendong Li, Wen Chen, Ziheng Zhang, Qingqing Wu, Huanqing Cao, Jun Li

Since the coupling of optimization variables, the whole optimization problem is non-convex and cannot be solved directly.

No driver, No Regulation? --Online Legal Driving Behavior Monitoring for Self-driving Vehicles

no code implementations8 Dec 2022 Wenhao Yu, Chengxiang Zhao, Jiaxin Liu, Yingkai Yang, Xiaohan Ma, Jun Li, Weida Wang, Hong Wang, Ding Zhao, Xiaosong Hu

To address these challenges, this paper aims to digitize traffic law comprehensively and provide an application for online monitoring of legal driving behavior for autonomous vehicles.

Autonomous Driving Decision Making

Curriculum Temperature for Knowledge Distillation

1 code implementation29 Nov 2022 Zheng Li, Xiang Li, Lingfeng Yang, Borui Zhao, RenJie Song, Lei Luo, Jun Li, Jian Yang

In this paper, we propose a simple curriculum-based technique, termed Curriculum Temperature for Knowledge Distillation (CTKD), which controls the task difficulty level during the student's learning career through a dynamic and learnable temperature.

Image Classification Knowledge Distillation

DesNet: Decomposed Scale-Consistent Network for Unsupervised Depth Completion

no code implementations20 Nov 2022 Zhiqiang Yan, Kun Wang, Xiang Li, Zhenyu Zhang, Jun Li, Jian Yang

Unsupervised depth completion aims to recover dense depth from the sparse one without using the ground-truth annotation.

Depth Completion Depth Estimation +1

Normal Transformer: Extracting Surface Geometry from LiDAR Points Enhanced by Visual Semantics

no code implementations19 Nov 2022 Ancheng Lin, Jun Li

High-quality estimation of surface normal can help reduce ambiguity in many geometry understanding problems, such as collision avoidance and occlusion inference.

Information-guided pixel augmentation for pixel-wise contrastive learning

no code implementations14 Nov 2022 Quan Quan, Qingsong Yao, Jun Li, S. Kevin Zhou

To the best of our knowledge, we are the first to propose a pixel augmentation method with a pixel granularity for enhancing unsupervised pixel-wise contrastive learning.

Contrastive Learning Self-Supervised Learning

PeSOTIF: a Challenging Visual Dataset for Perception SOTIF Problems in Long-tail Traffic Scenarios

1 code implementation7 Nov 2022 Liang Peng, Jun Li, Wenbo Shao, Hong Wang

Perception algorithms in autonomous driving systems confront great challenges in long-tail traffic scenarios, where the problems of Safety of the Intended Functionality (SOTIF) could be triggered by the algorithm performance insufficiencies and dynamic operational environment.

Autonomous Driving object-detection +1

Decentralized Federated Reinforcement Learning for User-Centric Dynamic TFDD Control

no code implementations4 Nov 2022 Ziyan Yin, Zhe Wang, Jun Li, Ming Ding, Wen Chen, Shi Jin

The explosive growth of dynamic and heterogeneous data traffic brings great challenges for 5G and beyond mobile networks.

Federated Learning reinforcement-learning +1

A Cooperative Perception System Robust to Localization Errors

no code implementations12 Oct 2022 Zhiying Song, Fuxi Wen, Hailiang Zhang, Jun Li

We propose a distributed object-level cooperative perception system called OptiMatch, in which the detected 3D bounding boxes and local state information are shared between the connected vehicles.

Autonomous Driving

Progress and Prospects for Fairness in Healthcare and Medical Image Analysis

no code implementations27 Sep 2022 Zikang Xu, Jun Li, Qingsong Yao, S. Kevin Zhou

Machine learning-enabled medical imaging analysis has become a vital part of the current automatic diagnosis system.

Fairness object-detection +1

CAMO-MOT: Combined Appearance-Motion Optimization for 3D Multi-Object Tracking with Camera-LiDAR Fusion

no code implementations6 Sep 2022 Li Wang, Xinyu Zhang, Wenyuan Qin, Xiaoyu Li, Lei Yang, Zhiwei Li, Lei Zhu, Hong Wang, Jun Li, Huaping Liu

As such, we propose a novel camera-LiDAR fusion 3D MOT framework based on the Combined Appearance-Motion Optimization (CAMO-MOT), which uses both camera and LiDAR data and significantly reduces tracking failures caused by occlusion and false detection.

3D Multi-Object Tracking Autonomous Driving +1

Global Attention-based Encoder-Decoder LSTM Model for Temperature Prediction of Permanent Magnet Synchronous Motors

no code implementations30 Jul 2022 Jun Li, Thangarajah Akilan

Temperature monitoring is critical for electrical motors to determine if device protection measures should be executed.

Network medicine framework reveals generic herb-symptom effectiveness of Traditional Chinese Medicine

no code implementations18 Jul 2022 Xiao Gan, Zixin Shu, Xinyan Wang, Dengying Yan, Jun Li, Shany ofaim, Réka Albert, XiaoDong Li, Baoyan Liu, Xuezhong Zhou, Albert-László Barabási

We validate our framework with real-world hospital patient data by showing that (1) shorter network distance between symptoms of inpatients correlates with higher relative risk (co-occurrence), and (2) herb-symptom network proximity is indicative of patients' symptom recovery rate after herbal treatment.

Mix-Teaching: A Simple, Unified and Effective Semi-Supervised Learning Framework for Monocular 3D Object Detection

1 code implementation10 Jul 2022 Lei Yang, Xinyu Zhang, Li Wang, Minghan Zhu, Chuang Zhang, Jun Li

Besides, by leveraging full training set and the additional 48K raw images of KITTI, it can further improve the MonoFlex by +4. 65% improvement on AP@0. 7 for car detection, reaching 18. 54% AP@0. 7, which ranks the 1st place among all monocular based methods on KITTI test leaderboard.

Autonomous Driving Model Optimization +2

Lesion-Aware Contrastive Representation Learning for Histopathology Whole Slide Images Analysis

1 code implementation27 Jun 2022 Jun Li, Yushan Zheng, Kun Wu, Jun Shi, Fengying Xie, Zhiguo Jiang

In this paper, we proposed a novel contrastive representation learning framework named Lesion-Aware Contrastive Learning (LACL) for histopathology whole slide image analysis.

Contrastive Learning Representation Learning +1

Kernel Attention Transformer (KAT) for Histopathology Whole Slide Image Classification

1 code implementation27 Jun 2022 Yushan Zheng, Jun Li, Jun Shi, Fengying Xie, Zhiguo Jiang

Transformer has been widely used in histopathology whole slide image (WSI) classification for the purpose of tumor grading, prognosis analysis, etc.

Classification Image Classification

A Self-Guided Framework for Radiology Report Generation

no code implementations19 Jun 2022 Jun Li, Shibo Li, Ying Hu, Huiren Tao

Moreover, SGF successfully improves the accuracy and length of medical report generation by incorporating a similarity comparison mechanism that imitates the process of human self-improvement through compar-ative practice.

Image Captioning Medical Report Generation

Design of optical voltage sensor based on electric field regulation and rotating isomerism electrode

no code implementations14 Jun 2022 Jun Li, Yifan Lin, Nan Xie

This technology could shift the measured signal frequency band from near 50 Hz moved to several kilometer Hz, so as to make the output signal avoid the interference from low-frequency temperature drift, stress birefringence and vibration, leading to higher stability and reliability.

CompleteDT: Point Cloud Completion with Dense Augment Inference Transformers

no code implementations30 May 2022 Jun Li, Shangwei Guo, Shaokun Han

Point cloud completion task aims to predict the missing part of incomplete point clouds and generate complete point clouds with details.

Point Cloud Completion

Providing Location Information at Edge Networks: A Federated Learning-Based Approach

no code implementations17 May 2022 Xin Cheng, Tingting Liu, Feng Shu, Chuan Ma, Jun Li, Jiangzhou Wang

Recently, the development of mobile edge computing has enabled exhilarating edge artificial intelligence (AI) with fast response and low communication cost.

Edge-computing Federated Learning +1

A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model

no code implementations ICLR 2022 Jianwen Xie, Yaxuan Zhu, Jun Li, Ping Li

Under the short-run non-mixing MCMC scenario, the estimation of the energy-based model is shown to follow the perturbation of maximum likelihood, and the short-run Langevin flow and the normalizing flow form a two-flow generator that we call CoopFlow.

CoDo: Contrastive Learning with Downstream Background Invariance for Detection

no code implementations10 May 2022 Bing Zhao, Jun Li, Hong Zhu

To bridge the performance gap, we propose a novel object-level self-supervised learning method, called Contrastive learning with Downstream background invariance (CoDo).

Contrastive Learning Data Augmentation +5

Optical Remote Sensing Image Understanding with Weak Supervision: Concepts, Methods, and Perspectives

no code implementations18 Apr 2022 Jun Yue, Leyuan Fang, Pedram Ghamisi, Weiying Xie, Jun Li, Jocelyn Chanussot, Antonio J Plaza

Therefore, remote sensing image understanding often faces the problems of incomplete, inexact, and inaccurate supervised information, which will affect the breadth and depth of remote sensing applications.

Change Detection Image Classification +4

A3CLNN: Spatial, Spectral and Multiscale Attention ConvLSTM Neural Network for Multisource Remote Sensing Data Classification

no code implementations9 Apr 2022 Heng-Chao Li, Wen-Shuai Hu, Wei Li, Jun Li, Qian Du, Antonio Plaza

The problem of effectively exploiting the information multiple data sources has become a relevant but challenging research topic in remote sensing.

Transfer Learning

MC-UNet Multi-module Concatenation based on U-shape Network for Retinal Blood Vessels Segmentation

1 code implementation7 Apr 2022 Ting Zhang, Jun Li, Yi Zhao, Nan Chen, Han Zhou, Hongtao Xu, Zihao Guan, Changcai Yang, Lanyan Xue, Riqing Chen, Lifang Wei

The proposed network structure retains three layers the essential structure of U-Net, in which the atrous convolution combining the multi-kernel pooling blocks are designed to obtain more contextual information.

Semi-Data-Aided Channel Estimation for MIMO Systems via Reinforcement Learning

no code implementations3 Apr 2022 Tae-Kyoung Kim, Yo-Seb Jeon, Jun Li, Nima Tavangaran, H. Vincent Poor

Data-aided channel estimation is a promising solution to improve channel estimation accuracy by exploiting data symbols as pilot signals for updating an initial channel estimate.

reinforcement-learning Reinforcement Learning (RL)

Energy-Efficient IRS-Aided NOMA Beamforming for 6G Wireless Communications

no code implementations30 Mar 2022 Asim Ihsan, Wen Chen, Muhammad Asif, Wali Ullah Khan, Jun Li

This manuscript presents an energy-efficient alternating optimization framework based on intelligent reflective surfaces (IRS) aided non-orthogonal multiple access beamforming (NOMA-BF) system for 6G wireless communications.

Nested Collaborative Learning for Long-Tailed Visual Recognition

1 code implementation CVPR 2022 Jun Li, Zichang Tan, Jun Wan, Zhen Lei, Guodong Guo

NCL consists of two core components, namely Nested Individual Learning (NIL) and Nested Balanced Online Distillation (NBOD), which focus on the individual supervised learning for each single expert and the knowledge transferring among multiple experts, respectively.

Image Classification Long-tail Learning

Federated Learning-Based Localization with Heterogeneous Fingerprint Database

no code implementations29 Mar 2022 Xin Cheng, Chuan Ma, Jun Li, Haiwei Song, Feng Shu, Jiangzhou Wang

Fingerprint-based localization plays an important role in indoor location-based services, where the position information is usually collected in distributed clients and gathered in a centralized server.

Federated Learning

Industrial Style Transfer with Large-scale Geometric Warping and Content Preservation

1 code implementation CVPR 2022 Jinchao Yang, Fei Guo, Shuo Chen, Jun Li, Jian Yang

Given a source product, a target product, and an art style image, our method produces a neural warping field that warps the source shape to imitate the geometric style of the target and a neural texture transformation network that transfers the artistic style to the warped source product.

Style Transfer

Multi-Modal Masked Pre-Training for Monocular Panoramic Depth Completion

no code implementations18 Mar 2022 Zhiqiang Yan, Xiang Li, Kun Wang, Zhenyu Zhang, Jun Li, Jian Yang

To deal with the PDC task, we train a deep network that takes both depth and image as inputs for the dense panoramic depth recovery.

Depth Completion Transfer Learning

Universal Segmentation of 33 Anatomies

no code implementations4 Mar 2022 Pengbo Liu, Yang Deng, Ce Wang, Yuan Hui, Qian Li, Jun Li, Shiwei Luo, Mengke Sun, Quan Quan, Shuxin Yang, You Hao, Honghu Xiao, Chunpeng Zhao, Xinbao Wu, S. Kevin Zhou

Firstly, while it is ideal to learn such a model from a large-scale, fully-annotated dataset, it is practically hard to curate such a dataset.

Image Segmentation Medical Image Segmentation +1

MixCL: Pixel label matters to contrastive learning

no code implementations4 Mar 2022 Jun Li, Quan Quan, S. Kevin Zhou

It is essential for medical image analysis, which is often notorious for its lack of annotations.

Contrastive Learning Image Segmentation +2

A Deep Learning Approach to Predicting Ventilator Parameters for Mechanically Ventilated Septic Patients

no code implementations21 Feb 2022 Zhijun Zeng, Zhen Hou, Ting Li, Lei Deng, Jianguo Hou, Xinran Huang, Jun Li, Meirou Sun, Yunhan Wang, Qiyu Wu, Wenhao Zheng, Hua Jiang, Qi Wang

We develop a deep learning approach to predicting a set of ventilator parameters for a mechanically ventilated septic patient using a long and short term memory (LSTM) recurrent neural network (RNN) model.

Vertical Federated Learning: Challenges, Methodologies and Experiments

no code implementations9 Feb 2022 Kang Wei, Jun Li, Chuan Ma, Ming Ding, Sha Wei, Fan Wu, Guihai Chen, Thilina Ranbaduge

As a special architecture in FL, vertical FL (VFL) is capable of constructing a hyper ML model by embracing sub-models from different clients.

Federated Learning

Locally Random Alloy Codes with Channel Coding Theorems for Distributed Matrix Multiplication

no code implementations7 Feb 2022 Pedro Soto, Haibin Guan, Jun Li

Matrix multiplication is a fundamental operation in machine learning and is commonly distributed into multiple parallel tasks for large datasets.

Lightweight Projective Derivative Codes for Compressed Asynchronous Gradient Descent

no code implementations31 Jan 2022 Pedro Soto, Ilia Ilmer, Haibin Guan, Jun Li

Coded distributed computation has become common practice for performing gradient descent on large datasets to mitigate stragglers and other faults.

Temporal Transformer Networks with Self-Supervision for Action Recognition

no code implementations14 Dec 2021 Yongkang Zhang, Jun Li, Guoming Wu, Han Zhang, Zhiping Shi, Zhaoxun Liu, Zizhang Wu, Na Jiang

The temporal sequence self-supervision module we employ unprecedentedly adopts the streamlined strategy of "random batch random channel" to reverse the sequence of video frames, allowing robust extractions of motion information representation from inversed temporal dimensions and improving the generalization capability of the model.

Action Recognition Temporal Action Localization

Which images to label for few-shot medical landmark detection?

no code implementations CVPR 2022 Quan Quan, Qingsong Yao, Jun Li, S. Kevin Zhou

We herein propose a novel Sample Choosing Policy (SCP) to select "the most worthy" images for annotation, in the context of few-shot medical landmark detection.

Few-Shot Learning

CT-block: a novel local and global features extractor for point cloud

no code implementations30 Nov 2021 Shangwei Guo, Jun Li, Zhengchao Lai, Xiantong Meng, Shaokun Han

Meanwhile, the transformer-branch performs offset-attention process on the whole point cloud to extract the global feature.

Point Cloud Classification

Fast and Light-Weight Network for Single Frame Structured Illumination Microscopy Super-Resolution

no code implementations17 Nov 2021 Xi Cheng, Jun Li, Qiang Dai, ZhenYong Fu, Jian Yang

In our SF-SIM, we propose a noise estimator which can effectively suppress the noise in the image and enable our method to work under the low light and short exposure environment, without the need for stacking multiple frames for non-local denoising.

Denoising Super-Resolution

RRNet: Relational Reasoning Network with Parallel Multi-scale Attention for Salient Object Detection in Optical Remote Sensing Images

2 code implementations27 Oct 2021 Runmin Cong, Yumo Zhang, Leyuan Fang, Jun Li, Yao Zhao, Sam Kwong

Salient object detection (SOD) for optical remote sensing images (RSIs) aims at locating and extracting visually distinctive objects/regions from the optical RSIs.

object-detection Object Detection +2

Constructing Orthogonal Convolutions in an Explicit Manner

no code implementations ICLR 2022 Tan Yu, Jun Li, Yunfeng Cai, Ping Li

A convolution layer with an orthogonal Jacobian matrix is 1-Lipschitz in the 2-norm, making the output robust to the perturbation in input.

Cooperative Task Offloading and Block Mining in Blockchain-based Edge Computing with Multi-agent Deep Reinforcement Learning

no code implementations29 Sep 2021 Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, H. Vincent Poor

The convergence of mobile edge computing (MEC) and blockchain is transforming the current computing services in mobile networks, by offering task offloading solutions with security enhancement empowered by blockchain mining.


$f$-Divergence Thermodynamic Variational Objective: a Deformed Geometry Perspective

no code implementations29 Sep 2021 Jun Li, Ping Li

In this paper, we propose a $f$-divergence Thermodynamic Variational Objective ($f$-TVO).

Variational Inference

Sampling Network Guided Cross-Entropy Method for Unsupervised Point Cloud Registration

1 code implementation ICCV 2021 Haobo Jiang, Yaqi Shen, Jin Xie, Jun Li, Jianjun Qian, Jian Yang

Based on the reward function, for each state, we then construct a fused score function to evaluate the sampled transformations, where we weight the current and future rewards of the transformations.

Point Cloud Registration

Elevation Angle-Dependent 3D Trajectory Design for Aerial RIS-aided Communication

no code implementations23 Aug 2021 Yifan Liu, Bin Duo, Qingqing Wu, Xiaojun Yuan, Jun Li, Yonghui Li

This paper investigates an aerial reconfigurable intelligent surface (RIS)-aided communication system under the probabilistic line-of-sight (LoS) channel, where an unmanned aerial vehicle (UAV) equipped with an RIS is deployed to assist two ground nodes in their information exchange.


6G Internet of Things: A Comprehensive Survey

no code implementations11 Aug 2021 Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, Dusit Niyato, Octavia Dobre, H. Vincent Poor

The sixth generation (6G) wireless communication networks are envisioned to revolutionize customer services and applications via the Internet of Things (IoT) towards a future of fully intelligent and autonomous systems.

Autonomous Driving

An optical biomimetic eyes with interested object imaging

no code implementations8 Aug 2021 Jun Li, Shimei Chen, Shangyuan Wang, Miao Lei, Xiaofang Dai, Chuangxue Liang, Kunyuan Xu, Shuxin Lin, Yuhui Li, Yuer Fan, Ting Zhong

We presented an optical system to perform imaging interested objects in complex scenes, like the creature easy see the interested prey in the hunt for complex environments.

object-detection Object Detection +2

RigNet: Repetitive Image Guided Network for Depth Completion

no code implementations29 Jul 2021 Zhiqiang Yan, Kun Wang, Xiang Li, Zhenyu Zhang, Jun Li, Jian Yang

However, blurry guidance in the image and unclear structure in the depth still impede the performance of the image guided frameworks.

Depth Completion Depth Estimation +1

Joint Communication and Trajectory Design for Intelligent Reflecting Surface Empowered UAV SWIPT Networks

no code implementations23 Jul 2021 Zhendong Li, Wen Chen, Huanqing Cao, Hongying Tang, Kunlun Wang, Jun Li

Aiming at the limited battery capacity of widely deployed low-power smart devices in the Internet-of-things (IoT), this paper proposes a novel intelligent reflecting surface (IRS) empowered unmanned aerial vehicle (UAV) simultaneous wireless information and power transfer (SWIPT) network framework, in which IRS is used to reconstruct the wireless channel to enhance the wireless energy transmission efficiency and coverage area of the UAV SWIPT networks.

Low-Latency Federated Learning over Wireless Channels with Differential Privacy

no code implementations20 Jun 2021 Kang Wei, Jun Li, Chuan Ma, Ming Ding, Cailian Chen, Shi Jin, Zhu Han, H. Vincent Poor

Then, we convert the MAMAB to a max-min bipartite matching problem at each communication round, by estimating rewards with the upper confidence bound (UCB) approach.

Federated Learning

IPS300+: a Challenging Multimodal Dataset for Intersection Perception System

no code implementations5 Jun 2021 Huanan Wang, Xinyu Zhang, Jun Li, Zhiwei Li, Lei Yang, Shuyue Pan, Yongqiang Deng

Through an IPS (Intersection Perception System) installed at the diagonal of the intersection, this paper proposes a high-quality multimodal dataset for the intersection perception task.

Federated Learning for Industrial Internet of Things in Future Industries

no code implementations31 May 2021 Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, Dusit Niyato, H. Vincent Poor

The Industrial Internet of Things (IIoT) offers promising opportunities to transform the operation of industrial systems and becomes a key enabler for future industries.

Federated Learning

An Extension of BIM Using AI: a Multi Working-Machines Pathfinding Solution

no code implementations14 May 2021 Yusheng Xiang, Kailun Liu, Tianqing Su, Jun Li, Shirui Ouyang, Samuel S. Mao, Marcus Geimer

In the practical implementation of a construction site, it is sensible to solve the problem with a hybrid solution; therefore, in our study, we proposed an algorithm based on a cutting-edge multi-pathfinding algorithm to enable the massive number of machines cooperation and offer the advice to modify the unreasonable part of the working site in the meantime.

Dynamic network analysis improves protein 3D structural classification

no code implementations14 May 2021 Khalique Newaz, Jacob Piland, Patricia L. Clark, Scott J. Emrich, Jun Li, Tijana Milenkovic

Here, we propose for the first time a way to model 3D structures of proteins as dynamic PSNs, with the hypothesis that this will improve upon the current state-of-the-art PSC approaches that are based on static PSNs (and thus upon the existing state-of-the-art sequence and other 3D structural approaches).


Federated Learning with Unreliable Clients: Performance Analysis and Mechanism Design

1 code implementation10 May 2021 Chuan Ma, Jun Li, Ming Ding, Kang Wei, Wen Chen, H. Vincent Poor

Owing to the low communication costs and privacy-promoting capabilities, Federated Learning (FL) has become a promising tool for training effective machine learning models among distributed clients.

Federated Learning

Lite-FPN for Keypoint-based Monocular 3D Object Detection

1 code implementation1 May 2021 Lei Yang, Xinyu Zhang, Li Wang, Minghan Zhu, Jun Li

3D object detection with a single image is an essential and challenging task for autonomous driving.

Autonomous Driving Monocular 3D Object Detection +1

ASPCNet: A Deep Adaptive Spatial Pattern Capsule Network for Hyperspectral Image Classification

no code implementations25 Apr 2021 Jinping Wang, Xiaojun Tan, JianHuang Lai, Jun Li, Canqun Xiang

Based on this observation, this paper proposes an adaptive spatial pattern capsule network (ASPCNet) architecture by developing an adaptive spatial pattern (ASP) unit, that can rotate the sampling location of convolutional kernels on the basis of an enlarged receptive field.

General Classification Hyperspectral Image Classification

Federated Learning for Internet of Things: A Comprehensive Survey

no code implementations16 Apr 2021 Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, H. Vincent Poor

The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of intelligent services and applications empowered by artificial intelligence (AI).

Federated Learning

Cross-Validated Tuning of Shrinkage Factors for MVDR Beamforming Based on Regularized Covariance Matrix Estimation

no code implementations5 Apr 2021 Lei Xie, Zishu He, Jun Tong, Jun Li, Jiangtao Xi

We propose leave-one-out cross-validation (LOOCV) choices for the shrinkage factors to optimize the beamforming performance, referred to as $\text{S}^2$CM-CV and STE-CV.

Anchor-Constrained Viterbi for Set-Supervised Action Segmentation

no code implementations CVPR 2021 Jun Li, Sinisa Todorovic

This paper is about action segmentation under weak supervision in training, where the ground truth provides only a set of actions present, but neither their temporal ordering nor when they occur in a training video.

Action Segmentation Temporal Sequences

Action Shuffle Alternating Learning for Unsupervised Action Segmentation

no code implementations CVPR 2021 Jun Li, Sinisa Todorovic

Our SSL trains an RNN to recognize positive and negative action sequences, and the RNN's hidden layer is taken as our new action-level feature embedding.

Action Segmentation Self-Supervised Learning

Potential Convolution: Embedding Point Clouds into Potential Fields

no code implementations5 Apr 2021 Dengsheng Chen, Haowen Deng, Jun Li, Duo Li, Yao Duan, Kai Xu

In this work, rather than defining a continuous or discrete kernel, we directly embed convolutional kernels into the learnable potential fields, giving rise to potential convolution.

3D Shape Classification Scene Segmentation

A novel multimodal fusion network based on a joint coding model for lane line segmentation

no code implementations20 Mar 2021 Zhenhong Zou, Xinyu Zhang, Huaping Liu, Zhiwei Li, Amir Hussain, Jun Li

There has recently been growing interest in utilizing multimodal sensors to achieve robust lane line segmentation.

Regularized Covariance Estimation for Polarization Radar Detection in Compound Gaussian Sea Clutter

no code implementations17 Mar 2021 Lei Xie, Zishu He, Jun Tong, Tianle Liu, Jun Li, Jiangtao Xi

This paper investigates regularized estimation of Kronecker-structured covariance matrices (CM) for polarization radar in sea clutter scenarios where the data are assumed to follow the complex, elliptically symmetric (CES) distributions with a Kronecker-structured CM.

S-AT GCN: Spatial-Attention Graph Convolution Network based Feature Enhancement for 3D Object Detection

2 code implementations15 Mar 2021 Li Wang, Chenfei Wang, Xinyu Zhang, Tianwei Lan, Jun Li

3D object detection plays a crucial role in environmental perception for autonomous vehicles, which is the prerequisite of decision and control.

3D Object Detection Autonomous Vehicles +1

Roles of the Narrow Electronic Band near the Fermi Level in 1$T$-TaS$_2$-Related Layered Materials

no code implementations11 Mar 2021 Chenhaoping Wen, Jingjing Gao, Yuan Xie, Qing Zhang, Pengfei Kong, Jinghui Wang, Yilan Jiang, Xuan Luo, Jun Li, Wenjian Lu, Yu-Ping Sun, Shichao Yan

4$H_{\rm b}$-TaS$_2$ is a superconducting compound with alternating 1$T$-TaS$_2$ and 1$H$-TaS$_2$ layers, where the 1$H$-TaS$_2$ layer has weak charge density wave (CDW) pattern and reduces the CDW coupling between the adjacent 1$T$-TaS$_2$ layers.

Mesoscale and Nanoscale Physics Materials Science

Covert Model Poisoning Against Federated Learning: Algorithm Design and Optimization

no code implementations28 Jan 2021 Kang Wei, Jun Li, Ming Ding, Chuan Ma, Yo-Seb Jeon, H. Vincent Poor

An attacker in FL may control a number of participant clients, and purposely craft the uploaded model parameters to manipulate system outputs, namely, model poisoning (MP).

Federated Learning Model Poisoning

Solving localized wave solutions of the derivative nonlinear Schrodinger equation using an improved PINN method

no code implementations21 Jan 2021 Juncai Pu, Jun Li, Yong Chen

On the bases of the improved method, the effects for different numbers of initial points sampled, residual collocation points sampled, network layers, neurons per hidden layer on the second order genuine rational soliton solution dynamics of the DNLS are considered, and the relevant analysis when the locally adaptive activation function chooses different initial values of scalable parameters are also exhibited in the simulation of the two-order rogue wave solution.

Pattern Formation and Solitons Exactly Solvable and Integrable Systems

Blockchain Assisted Decentralized Federated Learning (BLADE-FL): Performance Analysis and Resource Allocation

no code implementations18 Jan 2021 Jun Li, Yumeng Shao, Kang Wei, Ming Ding, Chuan Ma, Long Shi, Zhu Han, H. Vincent Poor

Focusing on this problem, we explore the impact of lazy clients on the learning performance of BLADE-FL, and characterize the relationship among the optimal K, the learning parameters, and the proportion of lazy clients.

Federated Learning

Robust Dynamical Decoupling for the Manipulation of a Spin Network via a Single Spin

no code implementations11 Jan 2021 Xiaodong Yang, Yunrui Ge, Bo Zhang, Jun Li

High-fidelity control of quantum systems is crucial for quantum information processing, but is often limited by perturbations from the environment and imperfections in the applied control fields.

Quantum Physics

Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Models

1 code implementation16 Dec 2020 Pengbo Liu, Hu Han, Yuanqi Du, Heqin Zhu, Yinhao Li, Feng Gu, Honghu Xiao, Jun Li, Chunpeng Zhao, Li Xiao, Xinbao Wu, S. Kevin Zhou

Due to the lack of a large-scale pelvic CT dataset with annotations, deep learning methods are not fully explored.

Blockchain Assisted Decentralized Federated Learning (BLADE-FL) with Lazy Clients

no code implementations2 Dec 2020 Jun Li, Yumeng Shao, Ming Ding, Chuan Ma, Kang Wei, Zhu Han, H. Vincent Poor

The proposed BLADE-FL has a good performance in terms of privacy preservation, tamper resistance, and effective cooperation of learning.

Federated Learning

Scalable Federated Learning over Passive Optical Networks

no code implementations29 Oct 2020 Jun Li, Lei Chen, Jiajia Chen

Two-step aggregation is introduced to facilitate scalable federated learning (SFL) over passive optical networks (PONs).

Networking and Internet Architecture

Reconstruction of Quantitative Susceptibility Maps from Phase of Susceptibility Weighted Imaging with Cross-Connected $Ψ$-Net

no code implementations12 Oct 2020 Zhiyang Lu, Jun Li, Zheng Li, Hongjian He, Jun Shi

In this work, we propose to explore a new value of the high-pass filtered phase data generated in susceptibility weighted imaging (SWI), and develop an end-to-end Cross-connected $\Psi$-Net (C$\Psi$-Net) to reconstruct QSM directly from these phase data in SWI without additional pre-processing.

When Federated Learning Meets Blockchain: A New Distributed Learning Paradigm

no code implementations20 Sep 2020 Chuan Ma, Jun Li, Ming Ding, Long Shi, Taotao Wang, Zhu Han, H. Vincent Poor

Motivated by the explosive computing capabilities at end user equipments, as well as the growing privacy concerns over sharing sensitive raw data, a new machine learning paradigm, named federated learning (FL) has emerged.

Networking and Internet Architecture

A Short Review on Data Modelling for Vector Fields

no code implementations1 Sep 2020 Jun Li, Wanrong Hong, Yusheng Xiang

On the application side, vector fields are an extremely useful type of data in empirical sciences, as well as signal processing, e. g. non-parametric transformations of 3D point clouds using 3D vector fields, the modelling of the fluid flow in earth science, and the modelling of physical fields.

LSOTB-TIR:A Large-Scale High-Diversity Thermal Infrared Object Tracking Benchmark

1 code implementation3 Aug 2020 Qiao Liu, Xin Li, Zhenyu He, Chenglong Li, Jun Li, Zikun Zhou, Di Yuan, Jing Li, Kai Yang, Nana Fan, Feng Zheng

We evaluate and analyze more than 30 trackers on LSOTB-TIR to provide a series of baselines, and the results show that deep trackers achieve promising performance.

Thermal Infrared Object Tracking Vocal Bursts Intensity Prediction

RDP-GAN: A Rényi-Differential Privacy based Generative Adversarial Network

1 code implementation4 Jul 2020 Chuan Ma, Jun Li, Ming Ding, Bo Liu, Kang Wei, Jian Weng, H. Vincent Poor

Generative adversarial network (GAN) has attracted increasing attention recently owing to its impressive ability to generate realistic samples with high privacy protection.

An Empirical Comparison of Unsupervised Constituency Parsing Methods

no code implementations ACL 2020 Jun Li, Yifan Cao, Jiong Cai, Yong Jiang, Kewei Tu

Unsupervised constituency parsing aims to learn a constituency parser from a training corpus without parse tree annotations.

Constituency Parsing

AReLU: Attention-based Rectified Linear Unit

1 code implementation24 Jun 2020 Dengsheng Chen, Jun Li, Kai Xu

Adding the attention module with a rectified linear unit (ReLU) results in an amplification of positive elements and a suppression of negative ones, both with learned, data-adaptive parameters.

Meta-Learning Transfer Learning

Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection

7 code implementations NeurIPS 2020 Xiang Li, Wenhai Wang, Lijun Wu, Shuo Chen, Xiaolin Hu, Jun Li, Jinhui Tang, Jian Yang

Specifically, we merge the quality estimation into the class prediction vector to form a joint representation of localization quality and classification, and use a vector to represent arbitrary distribution of box locations.

Dense Object Detection General Classification

Reconfigurable Intelligent Surface (RIS)-Enhanced Two-Way OFDM Communications

no code implementations5 May 2020 Chandan Pradhan, Ang Li, Lingyang Song, Jun Li, Branka Vucetic, Yonghui Li

In this paper, we focus on the reconfigurable intelligent surface (RIS)-enhanced two-way device-to-device (D2D) multi-pair orthogonal-frequency-division-multiplexing (OFDM) communication systems.

Vocal Bursts Valence Prediction

DNN-aided Read-voltage Threshold Optimization for MLC Flash Memory with Finite Block Length

no code implementations11 Apr 2020 Cheng Wang, Kang Wei, Lingjun Kong, Long Shi, Zhen Mei, Jun Li, Kui Cai

The error correcting performance of multi-level-cell (MLC) NAND flash memory is closely related to the block length of error correcting codes (ECCs) and log-likelihood-ratios (LLRs) of the read-voltage thresholds.

Learnable Subspace Clustering

1 code implementation9 Apr 2020 Jun Li, Hongfu Liu, Zhiqiang Tao, Handong Zhao, Yun Fu

This paper studies the large-scale subspace clustering (LSSC) problem with million data points.


A Compressive Sensing Approach for Federated Learning over Massive MIMO Communication Systems

no code implementations18 Mar 2020 Yo-Seb Jeon, Mohammad Mohammadi Amiri, Jun Li, H. Vincent Poor

One major challenge in system design is to reconstruct local gradient vectors accurately at the central server, which are computed-and-sent from the wireless devices.

Compressive Sensing Federated Learning +1

User-Level Privacy-Preserving Federated Learning: Analysis and Performance Optimization

no code implementations29 Feb 2020 Kang Wei, Jun Li, Ming Ding, Chuan Ma, Hang Su, Bo Zhang, H. Vincent Poor

According to our analysis, the UDP framework can realize $(\epsilon_{i}, \delta_{i})$-LDP for the $i$-th MT with adjustable privacy protection levels by varying the variances of the artificial noise processes.

Federated Learning Privacy Preserving

Set-Constrained Viterbi for Set-Supervised Action Segmentation

no code implementations CVPR 2020 Jun Li, Sinisa Todorovic

This paper is about weakly supervised action segmentation, where the ground truth specifies only a set of actions present in a training video, but not their true temporal ordering.

Action Segmentation Multiple Instance Learning

Vehicle Tracking in Wireless Sensor Networks via Deep Reinforcement Learning

no code implementations22 Feb 2020 Jun Li, Zhichao Xing, Weibin Zhang, Yan Lin, Feng Shu

Vehicle tracking has become one of the key applications of wireless sensor networks (WSNs) in the fields of rescue, surveillance, traffic monitoring, etc.

reinforcement-learning Reinforcement Learning (RL)

Face Hallucination with Finishing Touches

no code implementations9 Feb 2020 Yang Zhang, Ivor W. Tsang, Jun Li, Ping Liu, Xiaobo Lu, Xin Yu

The coarse-level FHnet generates a frontal coarse HR face and then the fine-level FHnet makes use of the facial component appearance prior, i. e., fine-grained facial components, to attain a frontal HR face image with authentic details.

Face Hallucination Face Recognition

Learning Canonical Shape Space for Category-Level 6D Object Pose and Size Estimation

no code implementations CVPR 2020 Dengsheng Chen, Jun Li, Zheng Wang, Kai Xu

To tackle intra-class shape variations, we learn canonical shape space (CASS), a unified representation for a large variety of instances of a certain object category.

3D Shape Representation Generating 3D Point Clouds

UAV-Enabled Confidential Data Collection in Wireless Networks

no code implementations3 Jan 2020 Xiaobo Zhou, Shihao Yan, Min Li, Jun Li, Feng Shu

This work, for the first time, considers confidential data collection in the context of unmanned aerial vehicle (UAV) wireless networks, where the scheduled ground sensor node (SN) intends to transmit confidential information to the UAV without being intercepted by other unscheduled ground SNs.

Naive Gabor Networks for Hyperspectral Image Classification

no code implementations9 Dec 2019 Chenying Liu, Jun Li, Lin He, Antonio J. Plaza, Shutao Li, Bo Li

Specifically, we develop an innovative phase-induced Gabor kernel, which is trickily designed to perform the Gabor feature learning via a linear combination of local low-frequency and high-frequency components of data controlled by the kernel phase.

Classification General Classification +1

Curvilinear Distance Metric Learning

1 code implementation NeurIPS 2019 Shuo Chen, Lei Luo, Jian Yang, Chen Gong, Jun Li, Heng Huang

To address this issue, we first reveal that the traditional linear distance metric is equivalent to the cumulative arc length between the data pair's nearest points on the learned straight measurer lines.

Metric Learning

Lifelong Spectral Clustering

no code implementations27 Nov 2019 Gan Sun, Yang Cong, Qianqian Wang, Jun Li, Yun Fu

As a new spectral clustering task arrives, L2SC firstly transfers knowledge from both basis library and feature library to obtain encoding matrix, and further redefines the library base over time to maximize performance across all the clustering tasks.


Symplectic $(-2)$-spheres and the symplectomorphism group of small rational 4-manifolds, II

no code implementations25 Nov 2019 Jun Li, Tian-Jun Li, Weiwei Wu

For $(\mathbb{C} P^2 \# 5{\overline {\mathbb{C} P^2}},\omega)$, let $N_{\omega}$ be the number of $(-2)$-symplectic spherical homology classes. We completely determine the Torelli symplectic mapping class group (Torelli SMCG): the Torelli SMCG is trivial if $N_{\omega}>8$; it is $\pi_0(Diff^+(S^2, 5))$ if $N_{\omega}=0$ (by Paul Seidel and Jonathan Evans); it is $\pi_0(Diff^+(S^2, 4))$ in the remaining case.

Symplectic Geometry

Federated Learning with Differential Privacy: Algorithms and Performance Analysis

no code implementations1 Nov 2019 Kang Wei, Jun Li, Ming Ding, Chuan Ma, Howard H. Yang, Farokhi Farhad, Shi Jin, Tony Q. S. Quek, H. Vincent Poor

Specifically, the theoretical bound reveals the following three key properties: 1) There is a tradeoff between the convergence performance and privacy protection levels, i. e., a better convergence performance leads to a lower protection level; 2) Given a fixed privacy protection level, increasing the number $N$ of overall clients participating in FL can improve the convergence performance; 3) There is an optimal number of maximum aggregation times (communication rounds) in terms of convergence performance for a given protection level.

Federated Learning Privacy Preserving +1

LPRNet: Lightweight Deep Network by Low-rank Pointwise Residual Convolution

no code implementations25 Oct 2019 Bin Sun, Jun Li, Ming Shao, Yun Fu

To reduce the computation and memory costs, we propose a novel lightweight deep learning module by low-rank pointwise residual (LPR) convolution, called LPRNet.

Face Alignment Image Classification +1

Bandwidth Slicing to Boost Federated Learning in Edge Computing

no code implementations24 Oct 2019 Jun Li, Xiaoman Shen, Lei Chen, Jiajia Chen

Bandwidth slicing is introduced to support federated learning in edge computing to assure low communication delay for training traffic.

Edge-computing Federated Learning

Weighted graphlets and deep neural networks for protein structure classification

no code implementations7 Oct 2019 Hongyu Guo, Khalique Newaz, Scott Emrich, Tijana Milenkovic, Jun Li

We develop a weighted network that depicts the protein structures, and more importantly, we propose the first graphlet-based measure that applies to weighted networks.

Classification General Classification

Weakly Supervised Energy-Based Learning for Action Segmentation

1 code implementation ICCV 2019 Jun Li, Peng Lei, Sinisa Todorovic

This paper is about labeling video frames with action classes under weak supervision in training, where we have access to a temporal ordering of actions, but their start and end frames in training videos are unknown.

Video Segmentation Video Semantic Segmentation +1

Variable selection with false discovery rate control in deep neural networks

1 code implementation17 Sep 2019 Zixuan Song, Jun Li

Deep neural networks (DNNs) are famous for their high prediction accuracy, but they are also known for their black-box nature and poor interpretability.

Variable Selection

On Safeguarding Privacy and Security in the Framework of Federated Learning

no code implementations14 Sep 2019 Chuan Ma, Jun Li, Ming Ding, Howard Hao Yang, Feng Shu, Tony Q. S. Quek, H. Vincent Poor

Motivated by the advancing computational capacity of wireless end-user equipment (UE), as well as the increasing concerns about sharing private data, a new machine learning (ML) paradigm has emerged, namely federated learning (FL).

Networking and Internet Architecture

Cross-X Learning for Fine-Grained Visual Categorization

no code implementations ICCV 2019 Wei Luo, Xitong Yang, Xianjie Mo, Yuheng Lu, Larry S. Davis, Jun Li, Jian Yang, Ser-Nam Lim

Recognizing objects from subcategories with very subtle differences remains a challenging task due to the large intra-class and small inter-class variation.

Ranked #15 on Fine-Grained Image Classification on NABirds (using extra training data)

Fine-Grained Image Classification Fine-Grained Visual Categorization

Learning Part Generation and Assembly for Structure-aware Shape Synthesis

no code implementations16 Jun 2019 Jun Li, Chengjie Niu, Kai Xu

Enlightened by the fact that 3D shape structure is characterized as part composition and placement, we propose to model 3D shape variations with a part-aware deep generative network, coined as PAGENet.

Shakeout: A New Approach to Regularized Deep Neural Network Training

1 code implementation13 Apr 2019 Guoliang Kang, Jun Li, DaCheng Tao

Dropout has played an essential role in many successful deep neural networks, by inducing regularization in the model training.

Model Compression