Search Results for author: Kun Wang

Found 82 papers, 15 papers with code

LST-Net: Learning a Convolutional Neural Network with a Learnable Sparse Transform

no code implementations ECCV 2020 Lida Li, Kun Wang, Shuai Li, Xiangchu Feng, Lei Zhang

The 2D convolutional (Conv2d) layer is the fundamental element to a deep convolutional neural network (CNN).

Attend Who is Weak: Enhancing Graph Condensation via Cross-Free Adversarial Training

no code implementations27 Nov 2023 Xinglin Li, Kun Wang, Hanhui Deng, Yuxuan Liang, Di wu

We seminally propose the concept of Shock Absorber (a type of perturbation) that enhances the robustness and stability of the original graphs against changes in an adversarial training fashion.

Node Classification

Causal-Story: Local Causal Attention Utilizing Parameter-Efficient Tuning For Visual Story Synthesis

no code implementations18 Sep 2023 Tianyi Song, Jiuxin Cao, Kun Wang, Bo Liu, Xiaofeng Zhang

The current state-of-the-art method combines the features of historical captions, historical frames, and the current captions as conditions for generating the current frame.

Image Generation Story Generation

Towards Vehicle-to-everything Autonomous Driving: A Survey on Collaborative Perception

no code implementations31 Aug 2023 Si Liu, Chen Gao, Yuan Chen, Xingyu Peng, Xianghao Kong, Kun Wang, Runsheng Xu, Wentao Jiang, Hao Xiang, Jiaqi Ma, Miao Wang

Specifically, we analyze the performance changes of different methods under different bandwidths, providing a deep insight into the performance-bandwidth trade-off issue.

Autonomous Driving

The Snowflake Hypothesis: Training Deep GNN with One Node One Receptive field

no code implementations19 Aug 2023 Kun Wang, Guohao Li, Shilong Wang, Guibin Zhang, Kai Wang, Yang You, Xiaojiang Peng, Yuxuan Liang, Yang Wang

Despite Graph Neural Networks demonstrating considerable promise in graph representation learning tasks, GNNs predominantly face significant issues with over-fitting and over-smoothing as they go deeper as models of computer vision realm.

Graph Representation Learning

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

Safety Guaranteed Control for Spacecraft Inspection Mission

no code implementations8 Jun 2023 Kun Wang, Tao Meng, Jiakun Lei, Weijia Wang

In order to address this issue, we propose a control strategy based on control barrier functions, summarized as "safety check on kinematics" and "velocity tracking on dynamics" approach.

Composite Triggered Intermittent Control for Constrained Spacecraft Attitude Tracking

no code implementations31 May 2023 Jiakun Lei, Tao Meng, Kun Wang, Weijia Wang, Shujian Sun

Further, the basic intermittent attitude controller is extended to a "constrained version" by introducing a strictly bounded virtual control law and an input saturation compensation auxiliary system.


Adaptive Compatible Performance Control for Spacecraft Attitude Control under Motion Constraints with Guaranteed Accuracy

no code implementations31 May 2023 Jiakun Lei, Tao Meng, Yang Zhu, Kun Wang, Weijia Wang

To tackle this problem, we propose a modified framework called Compatible Performance Control (CPC), which integrates the Prescribed Performance Control (PPC) scheme with a contradiction detection and alleviation strategy.

ConES: Concept Embedding Search for Parameter Efficient Tuning Large Vision Language Models

no code implementations30 May 2023 Huahui Yi, Ziyuan Qin, Wei Xu, Miaotian Guo, Kun Wang, Shaoting Zhang, Kang Li, Qicheng Lao

To achieve this, we propose a Concept Embedding Search (ConES) approach by optimizing prompt embeddings -- without the need of the text encoder -- to capture the 'concept' of the image modality through a variety of task objectives.

Instance Segmentation Prompt Engineering +1

ArtGPT-4: Artistic Vision-Language Understanding with Adapter-enhanced MiniGPT-4

no code implementations12 May 2023 Zhengqing Yuan, Huiwen Xue, Xinyi Wang, Yongming Liu, Zhuanzhe Zhao, Kun Wang

However, training models on such a large scale is challenging, and finding datasets that match the model's scale is often difficult.

Siamese DETR

1 code implementation CVPR 2023 Zeren Chen, Gengshi Huang, Wei Li, Jianing Teng, Kun Wang, Jing Shao, Chen Change Loy, Lu Sheng

In this work, we present Siamese DETR, a Siamese self-supervised pretraining approach for the Transformer architecture in DETR.

MULTI-VIEW LEARNING Representation Learning

Explore the Power of Synthetic Data on Few-shot Object Detection

no code implementations23 Mar 2023 Shaobo Lin, Kun Wang, Xingyu Zeng, Rui Zhao

To construct a representative synthetic training dataset, we maximize the diversity of the selected images via a sample-based and cluster-based method.

Few-Shot Object Detection object-detection +1

FedREP: A Byzantine-Robust, Communication-Efficient and Privacy-Preserving Framework for Federated Learning

no code implementations9 Mar 2023 Yi-Rui Yang, Kun Wang, Wu-Jun Li

Based on ConSpar, we further propose a novel FL framework called FedREP, which is Byzantine-robust, communication-efficient and privacy-preserving.

Federated Learning Privacy Preserving

An Effective Crop-Paste Pipeline for Few-shot Object Detection

no code implementations28 Feb 2023 Shaobo Lin, Kun Wang, Xingyu Zeng, Rui Zhao

Specifically, we first discover the base images which contain the FP of novel categories and select a certain amount of samples from them for the base and novel categories balance.

Data Augmentation Few-Shot Object Detection +1

Oriented Object Detection in Optical Remote Sensing Images using Deep Learning: A Survey

no code implementations21 Feb 2023 Kun Wang, Zi Wang, Zhang Li, Ang Su, Xichao Teng, Minhao Liu, Qifeng Yu

Oriented object detection is one of the most fundamental and challenging tasks in remote sensing, aiming at locating the oriented objects of numerous predefined object categories.

object-detection Object Detection +1

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 +2

Event-Triggered Intermittent Prescribed Performance Control for Spacecraft Attitude Reorientation

no code implementations10 Nov 2022 Jiakun Lei, Tao Meng, Kun Wang, Weijia Wang, Zhonghe Jin

The prescribed performance control (PPC) scheme is often employed for the control with guaranteed performance.

R$^2$F: A General Retrieval, Reading and Fusion Framework for Document-level Natural Language Inference

1 code implementation22 Oct 2022 Hao Wang, Yixin Cao, Yangguang Li, Zhen Huang, Kun Wang, Jing Shao

Document-level natural language inference (DOCNLI) is a new challenging task in natural language processing, aiming at judging the entailment relationship between a pair of hypothesis and premise documents.

Natural Language Inference Retrieval

6N-DoF Pose Tracking for Tensegrity Robots

no code implementations29 May 2022 Shiyang Lu, William R. Johnson III, Kun Wang, Xiaonan Huang, Joran Booth, Rebecca Kramer-Bottiglio, Kostas Bekris

To ensure that the pose estimates of rigid elements are physically feasible, i. e., they are not resulting in collisions between rods or with the environment, physical constraints are introduced during the optimization.

Pose Estimation Pose Tracking

Network Traffic Anomaly Detection Method Based on Multi scale Residual Feature

no code implementations8 May 2022 Xueyuan Duan, Yu Fu, Kun Wang

To address the problem that traditional network traffic anomaly detection algorithms do not suffi-ciently mine potential features in long time domain, an anomaly detection method based on mul-ti-scale residual features of network traffic is proposed.

Anomaly Detection Traffic Classification

ERGO: Event Relational Graph Transformer for Document-level Event Causality Identification

no code implementations COLING 2022 Meiqi Chen, Yixin Cao, Kunquan Deng, Mukai Li, Kun Wang, Jing Shao, Yan Zhang

In this paper, we propose a novel Event Relational Graph TransfOrmer (ERGO) framework for DECI, which improves existing state-of-the-art (SOTA) methods upon two aspects.

Event Causality Identification Node Classification +1

Few-shot Forgery Detection via Guided Adversarial Interpolation

no code implementations12 Apr 2022 Haonan Qiu, Siyu Chen, Bei Gan, Kun Wang, Huafeng Shi, Jing Shao, Ziwei Liu

Notably, our method is also validated to be robust to choices of majority and minority forgery approaches.

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

Towards Robust 2D Convolution for Reliable Visual Recognition

no code implementations18 Mar 2022 Lida Li, Shuai Li, Kun Wang, Xiangchu Feng, Lei Zhang

2D convolution (Conv2d), which is responsible for extracting features from the input image, is one of the key modules of a convolutional neural network (CNN).

A Recurrent Differentiable Engine for Modeling Tensegrity Robots Trainable with Low-Frequency Data

no code implementations28 Feb 2022 Kun Wang, Mridul Aanjaneya, Kostas Bekris

A model of NASA's icosahedron SUPERballBot on MuJoCo is used as the ground truth system to collect training data.

Exploring Forensic Dental Identification with Deep Learning

1 code implementation NeurIPS 2021 Yuan Liang, Weikun Han, Liang Qiu, Chen Wu, Yiting shao, Kun Wang, Lei He

In this work, we pioneer to study deep learning for dental forensic identification based on panoramic radiographs.

INTERN: A New Learning Paradigm Towards General Vision

no code implementations16 Nov 2021 Jing Shao, Siyu Chen, Yangguang Li, Kun Wang, Zhenfei Yin, Yinan He, Jianing Teng, Qinghong Sun, Mengya Gao, Jihao Liu, Gengshi Huang, Guanglu Song, Yichao Wu, Yuming Huang, Fenggang Liu, Huan Peng, Shuo Qin, Chengyu Wang, Yujie Wang, Conghui He, Ding Liang, Yu Liu, Fengwei Yu, Junjie Yan, Dahua Lin, Xiaogang Wang, Yu Qiao

Enormous waves of technological innovations over the past several years, marked by the advances in AI technologies, are profoundly reshaping the industry and the society.

Pitch Preservation In Singing Voice Synthesis

no code implementations11 Oct 2021 Shujun Liu, Hai Zhu, Kun Wang, Huajun Wang

For the phoneme encoder, based on the analysis that same phonemes corresponding to varying pitches can produce similar pronunciations, this encoder is followed by an adversarially trained pitch classifier to enforce the identical phonemes with different pitches mapping into the same phoneme feature space.

Singing Voice Synthesis

X2Teeth: 3D Teeth Reconstruction from a Single Panoramic Radiograph

no code implementations30 Aug 2021 Yuan Liang, Weinan Song, Jiawei Yang, Liang Qiu, Kun Wang, Lei He

Different from single object reconstruction from photos, this task has the unique challenge of constructing multiple objects at high resolutions.

3D Reconstruction Anatomy +2

Domain Adaptation for Underwater Image Enhancement

1 code implementation22 Aug 2021 Zhengyong Wang, Liquan Shen, Mei Yu, Kun Wang, Yufei Lin, Mai Xu

However, these methods ignore the significant domain gap between the synthetic and real data (i. e., interdomain gap), and thus the models trained on synthetic data often fail to generalize well to real underwater scenarios.

Domain Adaptation Image Enhancement

FPB: Feature Pyramid Branch for Person Re-Identification

1 code implementation4 Aug 2021 Suofei Zhang, Zirui Yin, Xiofu Wu, Kun Wang, Quan Zhou, Bin Kang

In this paper, we propose a lightweight Feature Pyramid Branch (FPB) to extract features from different layers of networks and aggregate them in a bidirectional pyramid structure.

object-detection Object Detection +1

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

Cascading Bandit under Differential Privacy

no code implementations24 May 2021 Kun Wang, Jing Dong, Baoxiang Wang, Shuai Li, Shuo Shao

This paper studies \emph{differential privacy (DP)} and \emph{local differential privacy (LDP)} in cascading bandits.

A mm-Wave Patch Antenna with Broad Bandwidth and a Wide Angular Range

no code implementations17 May 2021 Jonas Kornprobst, Kun Wang, Gerhard Hamberger, Thomas F. Eibert

The wide half power beamwidth is achieved by suitably designed parasitic patches for the first resonant mode.

Conservative Contextual Combinatorial Cascading Bandit

no code implementations17 Apr 2021 Kun Wang, Canzhe Zhao, Shuai Li, Shuo Shao

We propose the novel \emph{conservative contextual combinatorial cascading bandit ($C^4$-bandit)}, a cascading online learning game which incorporates the conservative mechanism.

Decision Making Recommendation Systems

GaitSet: Cross-view Gait Recognition through Utilizing Gait as a Deep Set

1 code implementation5 Feb 2021 Hanqing Chao, Kun Wang, Yiwei He, Junping Zhang, Jianfeng Feng

In this paper, we present a novel perspective that utilizes gait as a deep set, which means that a set of gait frames are integrated by a global-local fused deep network inspired by the way our left- and right-hemisphere processes information to learn information that can be used in identification.

Gait Recognition

Atlas-aware ConvNetfor Accurate yet Robust Anatomical Segmentation

no code implementations2 Feb 2021 Yuan Liang, Weinan Song, Jiawei Yang, Liang Qiu, Kun Wang, Lei He

Second, we can largely boost the robustness of existing ConvNets, proved by: (i) testing on scans with synthetic pathologies, and (ii) training and evaluation on scans of different scanning setups across datasets.

Detecting and quantifying entanglement on near-term quantum devices

1 code implementation28 Dec 2020 Kun Wang, Zhixin Song, Xuanqiang Zhao, Zihe Wang, Xin Wang

Firstly, it decomposes a positive map into a combination of quantum operations implementable on near-term quantum devices.

Quantum Physics Strongly Correlated Electrons

Exploring Instance-Level Uncertainty for Medical Detection

no code implementations23 Dec 2020 Jiawei Yang, Yuan Liang, Yao Zhang, Weinan Song, Kun Wang, Lei He

The ability of deep learning to predict with uncertainty is recognized as key for its adoption in clinical routines.

Lung Nodule Detection

Sim2Sim Evaluation of a Novel Data-Efficient Differentiable Physics Engine for Tensegrity Robots

no code implementations10 Nov 2020 Kun Wang, Mridul Aanjaneya, Kostas Bekris

The results indicate that only 0. 25\% of ground truth data are needed to train a policy that works on the ground truth system when the differentiable engine is used for training against training the policy directly on the ground truth system.

Spring-Rod System Identification via Differentiable Physics Engine

no code implementations9 Nov 2020 Kun Wang, Mridul Aanjaneya, Kostas Bekris

We propose a novel differentiable physics engine for system identification of complex spring-rod assemblies.


What Have We Achieved on Text Summarization?

1 code implementation EMNLP 2020 Dandan Huang, Leyang Cui, Sen yang, Guangsheng Bao, Kun Wang, Jun Xie, Yue Zhang

Deep learning has led to significant improvement in text summarization with various methods investigated and improved ROUGE scores reported over the years.

Text Summarization

Single-Sideband Time-Modulated Phased Array With 2-bit Phased Shifters

no code implementations6 Oct 2020 Yanchang Gao, Gang Ni, Kun Wang, Yiqing Liu, Chong He, Ronghong Jin, Xianling Liang

The timemodulated module is implemented by adding periodic phase modulation to 2-bit phase shifters, which is simpler without performance loss compared to existing SSB time-modulated method.

Accurate Anchor Free Tracking

no code implementations13 Jun 2020 Shengyun Peng, Yunxuan Yu, Kun Wang, Lei He

Specifically, a target object is defined by a bounding box center, tracking offset, and object size.

Visual Object Tracking

Sequential Weakly Labeled Multi-Activity Localization and Recognition on Wearable Sensors using Recurrent Attention Networks

2 code implementations13 Apr 2020 Kun Wang, Jun He, Lei Zhang

Recently, several attention mechanisms are proposed to handle the weakly labeled human activity data, which do not require accurate data annotation.

Human Activity Recognition

A non-cooperative meta-modeling game for automated third-party calibrating, validating, and falsifying constitutive laws with parallelized adversarial attacks

no code implementations13 Apr 2020 Kun Wang, WaiChing Sun, Qiang Du

The evaluation of constitutive models, especially for high-risk and high-regret engineering applications, requires efficient and rigorous third-party calibration, validation and falsification.

reinforcement-learning Reinforcement Learning (RL)

Oral-3D: Reconstructing the 3D Bone Structure of Oral Cavity from 2D Panoramic X-ray

no code implementations18 Mar 2020 Weinan Song, Yuan Liang, Jiawei Yang, Kun Wang, Lei He

In this paper, we propose a framework, named Oral-3D, to reconstruct the 3D oral cavity from a single PX image and prior information of the dental arch.

3D Reconstruction

Adapting Object Detectors with Conditional Domain Normalization

no code implementations ECCV 2020 Peng Su, Kun Wang, Xingyu Zeng, Shixiang Tang, Dapeng Chen, Di Qiu, Xiaogang Wang

Then this domain-vector is used to encode the features from another domain through a conditional normalization, resulting in different domains' features carrying the same domain attribute.

3D Object Detection Unsupervised Domain Adaptation

T-Net: Learning Feature Representation with Task-specific Supervision for Biomedical Image Analysis

no code implementations19 Feb 2020 Weinan Song, Yuan Liang, Jiawei Yang, Kun Wang, Lei He

The encoder-decoder network is widely used to learn deep feature representations from pixel-wise annotations in biomedical image analysis.

Region Proposal Representation Learning

Towards the standardization of quantum state verification using optimal strategies

no code implementations3 Feb 2020 Xinhe Jiang, Kun Wang, Kaiyi Qian, Zhaozhong Chen, Zhiyu Chen, Liangliang Lu, Lijun Xia, Fangmin Song, Shining Zhu, Xiaosong Ma

We experimentally obtain the scaling parameter of $r=-0. 88\pm$0. 03 and $-0. 78\pm$0. 07 for nonadaptive and adaptive strategies, respectively.

Quantum Physics Optics

Effective Scaling of Blockchain Beyond Consensus Innovations and Moore's Law

no code implementations7 Jan 2020 Yinqiu Liu, Kai Qian, Jianli Chen, Kun Wang, Lei He

As an emerging technology, blockchain has achieved great success in numerous application scenarios, from intelligent healthcare to smart cities.

Cryptography and Security Distributed, Parallel, and Cluster Computing 68M14 C.2.2

Reconstruction-Aware Imaging System Ranking by use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference

no code implementations14 May 2019 Yujia Chen, Yang Lou, Kun Wang, Matthew A. Kupinski, Mark A. Anastasio

In this work, a sparsity-driven observer (SDO) that can be employed to optimize hardware by use of a stochastic object model describing object sparsity is described and investigated.

Bayesian Inference Compressive Sensing +2

Time-sync Video Tag Extraction Using Semantic Association Graph

no code implementations3 May 2019 Wenmian Yang, Kun Wang, Na Ruan, Wenyuan Gao, Weijia Jia, Wei Zhao, Nan Liu, Yunyong Zhang

Finally, we gain the weight of each word by combining Semantic Weight (SW) and Inverse Document Frequency (IDF).


Attention-based Convolutional Neural Network for Weakly Labeled Human Activities Recognition with Wearable Sensors

no code implementations24 Mar 2019 Kun Wang, Jun He, Lei Zhang

Unlike images or videos data which can be easily labeled by human being, sensor data annotation is a time-consuming process.

Human Activity Recognition

A cooperative game for automated learning of elasto-plasticity knowledge graphs and models with AI-guided experimentation

no code implementations8 Mar 2019 Kun Wang, WaiChing Sun, Qiang Du

We introduce a multi-agent meta-modeling game to generate data, knowledge, and models that make predictions on constitutive responses of elasto-plastic materials.

Knowledge Graphs reinforcement-learning +1

Meta-modeling game for deriving theoretical-consistent, micro-structural-based traction-separation laws via deep reinforcement learning

no code implementations24 Oct 2018 Kun Wang, WaiChing Sun

This paper presents a new meta-modeling framework to employ deep reinforcement learning (DRL) to generate mechanical constitutive models for interfaces.

Game of Go

Ricean K-factor Estimation based on Channel Quality Indicator in OFDM Systems using Neural Network

no code implementations15 Aug 2018 Kun Wang

Ricean channel model is widely used in wireless communications to characterize the channels with a line-of-sight path.

General Classification

Scene Graph Generation from Objects, Phrases and Region Captions

1 code implementation ICCV 2017 Yikang Li, Wanli Ouyang, Bolei Zhou, Kun Wang, Xiaogang Wang

Object detection, scene graph generation and region captioning, which are three scene understanding tasks at different semantic levels, are tied together: scene graphs are generated on top of objects detected in an image with their pairwise relationship predicted, while region captioning gives a language description of the objects, their attributes, relations, and other context information.

Graph Generation object-detection +3

Crafting GBD-Net for Object Detection

1 code implementation8 Oct 2016 Xingyu Zeng, Wanli Ouyang, Junjie Yan, Hongsheng Li, Tong Xiao, Kun Wang, Yu Liu, Yucong Zhou, Bin Yang, Zhe Wang, Hui Zhou, Xiaogang Wang

The effectiveness of GBD-Net is shown through experiments on three object detection datasets, ImageNet, Pascal VOC2007 and Microsoft COCO.

object-detection Object Detection

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