Search Results for author: Lin Wang

Found 100 papers, 29 papers with code

Plan-CVAE: A Planning-based Conditional Variational Autoencoder for Story Generation

no code implementations CCL 2020 Lin Wang, Juntao Li, Rui Yan, Dongyan Zhao

Story generation is a challenging task of automatically creating natural languages to describe a sequence of events, which requires outputting text with not only a consistent topic but also novel wordings.

Story Generation

SRFNet: Monocular Depth Estimation with Fine-grained Structure via Spatial Reliability-oriented Fusion of Frames and Events

no code implementations22 Sep 2023 Tianbo Pan, Zidong Cao, Lin Wang

Firstly, we propose an attention-based interactive fusion (AIF) module that applies spatial priors of events and frames as the initial masks and learns the consensus regions to guide the inter-modal feature fusion.

Monocular Depth Estimation Robot Navigation

Chasing Day and Night: Towards Robust and Efficient All-Day Object Detection Guided by an Event Camera

no code implementations17 Sep 2023 Jiahang Cao, Xu Zheng, Yuanhuiyi Lyu, Jiaxu Wang, Renjing Xu, Lin Wang

The ability to detect objects in all lighting (i. e., normal-, over-, and under-exposed) conditions is crucial for real-world applications, such as self-driving. Traditional RGB-based detectors often fail under such varying lighting conditions. Therefore, recent works utilize novel event cameras to supplement or guide the RGB modality; however, these methods typically adopt asymmetric network structures that rely predominantly on the RGB modality, resulting in limited robustness for all-day detection.

object-detection Object Detection +1

IPA: Inference Pipeline Adaptation to Achieve High Accuracy and Cost-Efficiency

no code implementations24 Aug 2023 Saeid Ghafouri, Kamran Razavi, Mehran Salmani, Alireza Sanaee, Tania Lorido-Botran, Lin Wang, Joseph Doyle, Pooyan Jamshidi

To address this challenge and propose a solution to efficiently manage model variants in inference pipelines, we present IPA, an online deep-learning Inference Pipeline Adaptation system that efficiently leverages model variants for each deep learning task.

OmniZoomer: Learning to Move and Zoom in on Sphere at High-Resolution

no code implementations ICCV 2023 Zidong Cao, Hao Ai, Yan-Pei Cao, Ying Shan, XiaoHu Qie, Lin Wang

The M\"obius transformation is typically employed to further provide the opportunity for movement and zoom on ODIs, but applying it to the image level often results in blurry effect and aliasing problem.

Look at the Neighbor: Distortion-aware Unsupervised Domain Adaptation for Panoramic Semantic Segmentation

no code implementations ICCV 2023 Xu Zheng, Tianbo Pan, Yunhao Luo, Lin Wang

The aim is to tackle the domain gaps caused by the style disparities and distortion problem from the non-uniformly distributed pixels of equirectangular projection (ERP).

Semantic Segmentation Unsupervised Domain Adaptation

E-CLIP: Towards Label-efficient Event-based Open-world Understanding by CLIP

no code implementations6 Aug 2023 Jiazhou Zhou, Xu Zheng, Yuanhuiyi Lyu, Lin Wang

To this end, we first introduce a novel event encoder that subtly models the temporal information from events and meanwhile generates event prompts to promote the modality bridging.

Transfer Learning

Benchmarking and Analyzing Robust Point Cloud Recognition: Bag of Tricks for Defending Adversarial Examples

1 code implementation ICCV 2023 Qiufan Ji, Lin Wang, Cong Shi, Shengshan Hu, Yingying Chen, Lichao Sun

In this paper, we first establish a comprehensive, and rigorous point cloud adversarial robustness benchmark to evaluate adversarial robustness, which can provide a detailed understanding of the effects of the defense and attack methods.

Adversarial Robustness Benchmarking

Dynamic PlenOctree for Adaptive Sampling Refinement in Explicit NeRF

no code implementations ICCV 2023 Haotian Bai, Yiqi Lin, Yize Chen, Lin Wang

The explicit neural radiance field (NeRF) has gained considerable interest for its efficient training and fast inference capabilities, making it a promising direction such as virtual reality and gaming.

A Good Student is Cooperative and Reliable: CNN-Transformer Collaborative Learning for Semantic Segmentation

no code implementations ICCV 2023 Jinjing Zhu, Yunhao Luo, Xu Zheng, Hao Wang, Lin Wang

In this paper, we strive to answer the question "how to collaboratively learn convolutional neural network (CNN)-based and vision transformer (ViT)-based models by selecting and exchanging the reliable knowledge between them for semantic segmentation?"

Knowledge Distillation Semantic Segmentation

Coherent Compensation based ISAC Signal Processing for Long-range Sensing

no code implementations13 Jul 2023 Lin Wang, Zhiqing Wei, Liyan Su, Zhiyong Feng, Huici Wu, Dongsheng Xue

Integrated sensing and communication (ISAC) will greatly enhance the efficiency of physical resource utilization.

Test-Time Adaptation for Nighttime Color-Thermal Semantic Segmentation

no code implementations10 Jul 2023 Yexin Liu, Weiming Zhang, Guoyang Zhao, Jinjing Zhu, Athanasios Vasilakos, Lin Wang

we propose the first test-time adaptation (TTA) framework, dubbed Night-TTA, to address the problems for nighttime RGBT semantic segmentation without access to the source (daytime) data during adaptation.

Scene Understanding Semantic Segmentation

InferTurbo: A Scalable System for Boosting Full-graph Inference of Graph Neural Network over Huge Graphs

no code implementations1 Jul 2023 Dalong Zhang, Xianzheng Song, Zhiyang Hu, Yang Li, Miao Tao, Binbin Hu, Lin Wang, Zhiqiang Zhang, Jun Zhou

Inspired by the philosophy of ``think-like-a-vertex", a GAS-like (Gather-Apply-Scatter) schema is proposed to describe the computation paradigm and data flow of GNN inference.


Self-supervised Learning of Event-guided Video Frame Interpolation for Rolling Shutter Frames

no code implementations27 Jun 2023 Yunfan Lu, Guoqiang Liang, Lin Wang

Although events possess high temporal resolution, beneficial for video frame interpolation (VFI), a hurdle in tackling this task is the lack of paired GS frames.

Self-Supervised Learning Video Frame Interpolation

When SAM Meets Sonar Images

1 code implementation25 Jun 2023 Lin Wang, Xiufen Ye, Liqiang Zhu, Weijie Wu, JianGuo Zhang, Huiming Xing, Chao Hu

Notably, there is a lack of research on the application of SAM to sonar imaging.

Semantic Segmentation

FMapping: Factorized Efficient Neural Field Mapping for Real-Time Dense RGB SLAM

no code implementations1 Jun 2023 Tongyan Hua, Haotian Bai, Zidong Cao, Lin Wang

We then propose the sliding window sampler to reduce uncertainty by incorporating coherent geometric cues from observed frames during map initialization to enhance convergence.

Towards Language-guided Interactive 3D Generation: LLMs as Layout Interpreter with Generative Feedback

no code implementations25 May 2023 Yiqi Lin, Hao Wu, Ruichen Wang, Haonan Lu, Xiaodong Lin, Hui Xiong, Lin Wang

Generating and editing a 3D scene guided by natural language poses a challenge, primarily due to the complexity of specifying the positional relations and volumetric changes within the 3D space.

Learning INR for Event-guided Rolling Shutter Frame Correction, Deblur, and Interpolation

1 code implementation24 May 2023 Yunfan Lu, Guoqiang Liang, Lin Wang

Images captured by rolling shutter (RS) cameras under fast camera motion often contain obvious image distortions and blur, which can be modeled as a row-wise combination of a sequence of global shutter (GS) frames within the exposure time naturally, recovering high-frame-rate GS sharp frames from an RS blur image needs to simultaneously consider RS correction, deblur, and frame interpolation Taking this task is nontrivial, and to our knowledge, no feasible solutions exist by far.

Image Restoration

SPP-CNN: An Efficient Framework for Network Robustness Prediction

no code implementations13 May 2023 Chengpei Wu, Yang Lou, Lin Wang, Junli Li, Xiang Li, Guanrong Chen

This paper addresses the robustness of a network to sustain its connectivity and controllability against malicious attacks.

Deep Reinforcement Learning Based Resource Allocation for Cloud Native Wireless Network

no code implementations10 May 2023 Lin Wang, Jiasheng Wu, Yue Gao, Jingjing Zhang

Cloud native technology has revolutionized 5G beyond and 6G communication networks, offering unprecedented levels of operational automation, flexibility, and adaptability.

Cloud Computing Edge-computing +1

360$^\circ$ High-Resolution Depth Estimation via Uncertainty-aware Structural Knowledge Transfer

no code implementations17 Apr 2023 Zidong Cao, Hao Ai, Lin Wang

Our key idea is to transfer the scene structural knowledge from the readily available HR image modality and the corresponding LR depth maps to achieve the goal of HR depth estimation without extra inference cost.

Monocular Depth Estimation Scene Understanding +2

Towards Open-Scenario Semi-supervised Medical Image Classification

no code implementations8 Apr 2023 Lie Ju, Yicheng Wu, Wei Feng, Zhen Yu, Lin Wang, Zhuoting Zhu, ZongYuan Ge

Therefore, in this paper, we proposed a unified framework to leverage these unseen unlabeled data for open-scenario semi-supervised medical image classification.

Domain Adaptation Image Classification +1

Both Style and Distortion Matter: Dual-Path Unsupervised Domain Adaptation for Panoramic Semantic Segmentation

no code implementations CVPR 2023 Xu Zheng, Jinjing Zhu, Yexin Liu, Zidong Cao, Chong Fu, Lin Wang

Moreover, adversarial intra-projection training is proposed to reduce the inherent gap, between the features of the pinhole images and those of the ERP and TP images, respectively.

Scene Understanding Semantic Segmentation +1

CompoNeRF: Text-guided Multi-object Compositional NeRF with Editable 3D Scene Layout

no code implementations24 Mar 2023 Haotian Bai, Yuanhuiyi Lyu, Lutao Jiang, Sijia Li, Haonan Lu, Xiaodong Lin, Lin Wang

To address it, we propose a novel framework, dubbed CompoNeRF, to explicitly incorporates an editable 3D scene layout to provide effective guidance at the object (i. e., local) and scene (i. e., global) levels.

Text to 3D

Patch-Mix Transformer for Unsupervised Domain Adaptation: A Game Perspective

1 code implementation CVPR 2023 Jinjing Zhu, Haotian Bai, Lin Wang

We solve this problem from a game theory's perspective with the proposed model dubbed as PMTrans, which bridges source and target domains with an intermediate domain.

Unsupervised Domain Adaptation

Variantional autoencoder with decremental information bottleneck for disentanglement

no code implementations22 Mar 2023 Jiantao Wu, Shentong Mo, Muhammad Awais, Sara Atito, Xingshen Zhang, Lin Wang, Xiang Yang

One major challenge of disentanglement learning with variational autoencoders is the trade-off between disentanglement and reconstruction fidelity.


HRDFuse: Monocular 360°Depth Estimation by Collaboratively Learning Holistic-with-Regional Depth Distributions

no code implementations21 Mar 2023 Hao Ai, Zidong Cao, Yan-Pei Cao, Ying Shan, Lin Wang

Depth estimation from a monocular 360{\deg} image is a burgeoning problem owing to its holistic sensing of a scene.

Depth Estimation

Deep Learning for Event-based Vision: A Comprehensive Survey and Benchmarks

no code implementations17 Feb 2023 Xu Zheng, Yexin Liu, Yunfan Lu, Tongyan Hua, Tianbo Pan, Weiming Zhang, DaCheng Tao, Lin Wang

Being capable of capturing information in challenging visual conditions, event cameras have the potential to overcome the limitations of frame-based cameras in the computer vision and robotics community.

Event-based vision Image Reconstruction +3

A Fast Bootstrap Algorithm for Causal Inference with Large Data

1 code implementation6 Feb 2023 Matthew Kosko, Lin Wang, Michele Santacatterina

The bag of little bootstraps has been proposed in non-causal settings for large data but has not yet been applied to evaluate the properties of estimators of causal effects.

Causal Inference

FedEBA+: Towards Fair and Effective Federated Learning via Entropy-Based Model

no code implementations29 Jan 2023 Lin Wang, Zhichao Wang, Xiaoying Tang

Ensuring fairness is a crucial aspect of Federated Learning (FL), which enables the model to perform consistently across all clients.

Fairness Federated Learning

Multi-scale multi-modal micro-expression recognition algorithm based on transformer

no code implementations8 Jan 2023 Fengping Wang, Jie Li, Chun Qi, Lin Wang, Pan Wang

A micro-expression is a spontaneous unconscious facial muscle movement that can reveal the true emotions people attempt to hide.

Contrastive Learning Micro Expression Recognition +2

Pixel is All You Need: Adversarial Trajectory-Ensemble Active Learning for Salient Object Detection

no code implementations13 Dec 2022 Zhenyu Wu, Lin Wang, Wei Wang, Qing Xia, Chenglizhao Chen, Aimin Hao, Shuo Li

This paper attempts to answer this unexplored question by proving a hypothesis: there is a point-labeled dataset where saliency models trained on it can achieve equivalent performance when trained on the densely annotated dataset.

Active Learning Adversarial Attack +3

SEPT: Towards Scalable and Efficient Visual Pre-Training

no code implementations11 Dec 2022 Yiqi Lin, Huabin Zheng, Huaping Zhong, Jinjing Zhu, Weijia Li, Conghui He, Lin Wang

To address these issues, we build a task-specific self-supervised pre-training framework from a data selection perspective based on a simple hypothesis that pre-training on the unlabeled samples with similar distribution to the target task can bring substantial performance gains.


Autoregressive GNN-ODE GRU Model for Network Dynamics

no code implementations19 Nov 2022 Bo Liang, Lin Wang, Xiaofan Wang

In this paper, we propose an Autoregressive GNN-ODE GRU Model (AGOG) to learn and capture the continuous network dynamics and realize predictions of node states at an arbitrary time in a data-driven manner.

Time Series Analysis

Reconstruction of compressed spectral imaging based on global structure and spectral correlation

no code implementations27 Oct 2022 Pan Wang, Jie Li, Jieru Chen, Lin Wang, Chun Qi

To take full exploration of the constraints between spectra, the coefficients corresponding to the convolution kernel are constrained by the L_(2, 1)norm to improve spectral accuracy.


Synthetic Data Supervised Salient Object Detection

1 code implementation25 Oct 2022 Zhenyu Wu, Lin Wang, Wei Wang, Tengfei Shi, Chenglizhao Chen, Aimin Hao, Shuo Li

In this paper, we propose a novel yet effective method for SOD, coined SODGAN, which can generate infinite high-quality image-mask pairs requiring only a few labeled data, and these synthesized pairs can replace the human-labeled DUTS-TR to train any off-the-shelf SOD model.

Code Generation object-detection +2

3D Matting: A Benchmark Study on Soft Segmentation Method for Pulmonary Nodules Applied in Computed Tomography

no code implementations11 Oct 2022 Lin Wang, Xiufen Ye, Donghao Zhang, Wanji He, Lie Ju, Yi Luo, Huan Luo, Xin Wang, Wei Feng, Kaimin Song, Xin Zhao, ZongYuan Ge

In this work, we introduce the image matting into the 3D scenes and use the alpha matte, i. e., a soft mask, to describe lesions in a 3D medical image.

Binarization Image Matting

A Comprehensive Survey on Trustworthy Recommender Systems

no code implementations21 Sep 2022 Wenqi Fan, Xiangyu Zhao, Xiao Chen, Jingran Su, Jingtong Gao, Lin Wang, Qidong Liu, Yiqi Wang, Han Xu, Lei Chen, Qing Li

As one of the most successful AI-powered applications, recommender systems aim to help people make appropriate decisions in an effective and efficient way, by providing personalized suggestions in many aspects of our lives, especially for various human-oriented online services such as e-commerce platforms and social media sites.

Fairness Recommendation Systems

3D Matting: A Soft Segmentation Method Applied in Computed Tomography

no code implementations16 Sep 2022 Lin Wang, Xiufen Ye, Donghao Zhang, Wanji He, Lie Ju, Xin Wang, Wei Feng, Kaimin Song, Xin Zhao, ZongYuan Ge

It can be caused by many factors, such as the imaging properties, pathological anatomy, and the weak representation of the binary masks, which brings challenges to accurate 3D segmentation.

Anatomy Image Matting

Transformer-CNN Cohort: Semi-supervised Semantic Segmentation by the Best of Both Students

no code implementations6 Sep 2022 Xu Zheng, Yunhao Luo, Hao Wang, Chong Fu, Lin Wang

To this end, we propose class-aware feature consistency distillation (CFCD) that first leverages the outputs of each student as the pseudo labels and generates class-aware feature (CF) maps.

Semi-Supervised Semantic Segmentation

Joint Attention-Driven Domain Fusion and Noise-Tolerant Learning for Multi-Source Domain Adaptation

no code implementations5 Aug 2022 Tong Xu, Lin Wang, Wu Ning, Chunyan Lyu, Kejun Wang, Chenhui Wang

As a study on the efficient usage of data, Multi-source Unsupervised Domain Adaptation transfers knowledge from multiple source domains with labeled data to an unlabeled target domain.

Multi-Source Unsupervised Domain Adaptation Unsupervised Domain Adaptation

Efficient Video Deblurring Guided by Motion Magnitude

3 code implementations27 Jul 2022 Yusheng Wang, Yunfan Lu, Ye Gao, Lin Wang, Zhihang Zhong, Yinqiang Zheng, Atsushi Yamashita

Video deblurring is a highly under-constrained problem due to the spatially and temporally varying blur.

Deblurring Optical Flow Estimation

Unsupervised Domain Adaptive Fundus Image Segmentation with Category-level Regularization

1 code implementation8 Jul 2022 Wei Feng, Lin Wang, Lie Ju, Xin Zhao, Xin Wang, Xiaoyu Shi, ZongYuan Ge

Existing unsupervised domain adaptation methods based on adversarial learning have achieved good performance in several medical imaging tasks.

Image Segmentation Semantic Segmentation +1

Priors in Deep Image Restoration and Enhancement: A Survey

1 code implementation4 Jun 2022 Yunfan Lu, Yiqi Lin, Hao Wu, Yunhao Luo, Xu Zheng, Hui Xiong, Lin Wang

Image restoration and enhancement is a process of improving the image quality by removing degradations, such as noise, blur, and resolution degradation.

Image Restoration

DELTA: Diverse Client Sampling for Fasting Federated Learning

no code implementations27 May 2022 Lin Wang, Yongxin Guo, Tao Lin, Xiaoying Tang

However, an inadequate client sampling scheme can lead to the selection of unrepresentative subsets, resulting in significant variance in model updates and slowed convergence.

Federated Learning

Deep Learning for Omnidirectional Vision: A Survey and New Perspectives

1 code implementation21 May 2022 Hao Ai, Zidong Cao, Jinjing Zhu, Haotian Bai, Yucheng Chen, Lin Wang

Omnidirectional image (ODI) data is captured with a 360x180 field-of-view, which is much wider than the pinhole cameras and contains richer spatial information than the conventional planar images.

Autonomous Driving

Discriminative-Region Attention and Orthogonal-View Generation Model for Vehicle Re-Identification

no code implementations28 Apr 2022 Huadong Li, Yuefeng Wang, Ying WEI, Lin Wang, Li Ge

Finally, the distance between vehicle appearances is presented by the discriminative region features and multi-view features together.

Management Vehicle Re-Identification

Flexible Sampling for Long-tailed Skin Lesion Classification

no code implementations7 Apr 2022 Lie Ju, Yicheng Wu, Lin Wang, Zhen Yu, Xin Zhao, Xin Wang, Paul Bonnington, ZongYuan Ge

To address this, in this paper, we propose a curriculum learning-based framework called Flexible Sampling for the long-tailed skin lesion classification task.

Classification Lesion Classification +1

Unsignalized Intersection Management Strategy for Mixed Autonomy Traffic Streams

no code implementations7 Apr 2022 Junjie Zhou, Zhaokun Shen, Xiaofan Wang, Lin Wang

Combined with the designed vehicle planning and control algorithm, the unsignalized intersection management strategy consists of two parts: the heuristic priority queues based right of way allocation (HPQ) algorithm, and the vehicle planning and control algorithm.

Decision Making Management

Improving The Diagnosis of Thyroid Cancer by Machine Learning and Clinical Data

1 code implementation27 Mar 2022 Nan Miles Xi, Lin Wang, Chuanjia Yang

Current human assessment of thyroid nodule malignancy is prone to errors and may not guarantee an accurate preoperative diagnosis.

BIG-bench Machine Learning

A Learning Convolutional Neural Network Approach for Network Robustness Prediction

no code implementations20 Mar 2022 Yang Lou, Ruizi Wu, Junli Li, Lin Wang, Xiang Li, Guanrong Chen

Extensive experimental studies on both synthetic and real-world networks, both directed and undirected, demonstrate that 1) the proposed LFR-CNN performs better than other two state-of-the-art prediction methods, with significantly lower prediction errors; 2) LFR-CNN is insensitive to the variation of the network size, which significantly extends its applicability; 3) although LFR-CNN needs more time to perform feature learning, it can achieve accurate prediction faster than attack simulations; 4) LFR-CNN not only can accurately predict network robustness, but also provides a good indicator for connectivity robustness, better than the classical spectral measures.

Controllability of Multilayer Networked Sampled-data Systems

no code implementations4 Mar 2022 Zixuan Yang, Xiaofan Wang, Lin Wang

This paper explores the state controllability of multilayer networked sampled-data systems with inter-layer couplings, where zero-order holders (ZOHs) are on the control and transmission channels.

Controllability of Networked Sampled-data Systems

no code implementations18 Feb 2022 Zixuan Yang, Xiaofan Wang, Lin Wang

The controllability of networked sampled-data systems with zero-order holders on the control and transmission channels is explored, where single- and multi-rate sampling patterns are considered, respectively.

SphereSR: 360deg Image Super-Resolution With Arbitrary Projection via Continuous Spherical Image Representation

no code implementations CVPR 2022 Youngho Yoon, Inchul Chung, Lin Wang, Kuk-Jin Yoon

In this paper, we propose SphereSR, a novel framework to generate a continuous spherical image representation from an LR 360deg image, with the goal of predicting the RGB values at given spherical coordinates for superresolution with an arbitrary 360deg image projection.

Image Super-Resolution

SphereSR: 360° Image Super-Resolution with Arbitrary Projection via Continuous Spherical Image Representation

no code implementations13 Dec 2021 Youngho Yoon, Inchul Chung, Lin Wang, Kuk-Jin Yoon

We then propose a spherical local implicit image function (SLIIF) to predict RGB values at the spherical coordinates.

Image Super-Resolution

Event-guided Deblurring of Unknown Exposure Time Videos

no code implementations13 Dec 2021 Taewoo Kim, Jeongmin Lee, Lin Wang, Kuk-Jin Yoon

To this end, we first derive a new formulation for event-guided motion deblurring by considering the exposure and readout time in the video frame acquisition process.


BIPS: Bi-modal Indoor Panorama Synthesis via Residual Depth-aided Adversarial Learning

no code implementations12 Dec 2021 Changgyoon Oh, Wonjune Cho, Daehee Park, Yujeong Chae, Lin Wang, Kuk-Jin Yoon

Providing omnidirectional depth along with RGB information is important for numerous applications, eg, VR/AR.

EvDistill: Asynchronous Events to End-task Learning via Bidirectional Reconstruction-guided Cross-modal Knowledge Distillation

1 code implementation CVPR 2021 Lin Wang, Yujeong Chae, Sung-Hoon Yoon, Tae-Kyun Kim, Kuk-Jin Yoon

To enable KD across the unpaired modalities, we first propose a bidirectional modality reconstruction (BMR) module to bridge both modalities and simultaneously exploit them to distill knowledge via the crafted pairs, causing no extra computation in the inference.

Knowledge Distillation Object Recognition +1

Hierarchical Knowledge Guided Learning for Real-world Retinal Diseases Recognition

no code implementations17 Nov 2021 Lie Ju, Zhen Yu, Lin Wang, Xin Zhao, Xin Wang, Paul Bonnington, ZongYuan Ge

From a modeling perspective, most deep learning models trained on these datasets may lack the ability to generalize to rare diseases where only a few available samples are presented for training.

Knowledge Distillation

Deep Learning for HDR Imaging: State-of-the-Art and Future Trends

1 code implementation20 Oct 2021 Lin Wang, Kuk-Jin Yoon

High dynamic range (HDR) imaging is a technique that allows an extensive dynamic range of exposures, which is important in image processing, computer graphics, and computer vision.

SiamEvent: Event-based Object Tracking via Edge-aware Similarity Learning with Siamese Networks

1 code implementation28 Sep 2021 Yujeong Chae, Lin Wang, Kuk-Jin Yoon

Importantly, to find the part having the most similar edge structure of target, we propose to correlate the embedded events at two timestamps to compute the target edge similarity.

Motion Compensation Object Tracking

Investigating and Modeling the Dynamics of Long Ties

1 code implementation22 Sep 2021 Ding Lyu, Yuan Yuan, Lin Wang, Xiaofan Wang, Alex Pentland

Long ties, the social ties that bridge different communities, are widely believed to play crucial roles in spreading novel information in social networks.

Dual Transfer Learning for Event-based End-task Prediction via Pluggable Event to Image Translation

1 code implementation ICCV 2021 Lin Wang, Yujeong Chae, Kuk-Jin Yoon

Event cameras are novel sensors that perceive the per-pixel intensity changes and output asynchronous event streams with high dynamic range and less motion blur.

Depth Estimation Representation Learning +3

DQN Control Solution for KDD Cup 2021 City Brain Challenge

1 code implementation14 Aug 2021 Yitian Chen, Kunlong Chen, Kunjin Chen, Lin Wang

From our perspective, the major challenge of this competition is how to extend the classical DQN framework to traffic signals control in real-world complex road network and traffic flow situation.

Unsupervised Domain Adaptation for Retinal Vessel Segmentation with Adversarial Learning and Transfer Normalization

no code implementations4 Aug 2021 Wei Feng, Lie Ju, Lin Wang, Kaimin Song, Xin Wang, Xin Zhao, Qingyi Tao, ZongYuan Ge

In this work, we explore unsupervised domain adaptation in retinal vessel segmentation by using entropy-based adversarial learning and transfer normalization layer to train a segmentation network, which generalizes well across domains and requires no annotation of the target domain.

Retinal Vessel Segmentation Unsupervised Domain Adaptation

Medical Matting: A New Perspective on Medical Segmentation with Uncertainty

1 code implementation18 Jun 2021 Lin Wang, Lie Ju, Xin Wang, Wanji He, Donghao Zhang, Yelin Huang, Zhiwen Yang, Xuan Yao, Xin Zhao, Xiufen Ye, ZongYuan Ge

None of them investigate the influence of the ambiguous nature of the lesion itself. Inspired by image matting, this paper introduces alpha matte as a soft mask to represent uncertain areas in medical scenes and accordingly puts forward a new uncertainty quantification method to fill the gap of uncertainty research for lesion structure.

Image Matting Image Segmentation +2

Multi-Granularity Network with Modal Attention for Dense Affective Understanding

no code implementations18 Jun 2021 Baoming Yan, Lin Wang, Ke Gao, Bo Gao, Xiao Liu, Chao Ban, Jiang Yang, Xiaobo Li

Video affective understanding, which aims to predict the evoked expressions by the video content, is desired for video creation and recommendation.

Deconvolutional Density Network: Modeling Free-Form Conditional Distributions

1 code implementation29 May 2021 Bing Chen, Mazharul Islam, Jisuo Gao, Lin Wang

Conditional density estimation (CDE) is the task of estimating the probability of an event conditioned on some inputs.

Density Estimation

Unsupervised Dynamic Routing Via Competition Over Network Loss

no code implementations NeurIPS 2021 Lei Zhao, Lin Wang, Jiuqiao Yu

Using the self-organizing map over the competition of the loss of individual neural column, we route the input to the most appropriate modules dynamically, by doing this we separate the input functional space into different sub spaces which are represented by each individual neural column.


Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition

no code implementations22 Apr 2021 Lie Ju, Xin Wang, Lin Wang, Tongliang Liu, Xin Zhao, Tom Drummond, Dwarikanath Mahapatra, ZongYuan Ge

For example, there are estimated more than 40 different kinds of retinal diseases with variable morbidity, however with more than 30+ conditions are very rare from the global patient cohorts, which results in a typical long-tailed learning problem for deep learning-based screening models.

Knowledge Distillation

Surrogate-assisted cooperative signal optimization for large-scale traffic networks

no code implementations3 Mar 2021 Yongsheng Liang, Zhigang Ren, Lin Wang, Hanqing Liu, Wenhao Du

The decomposition operation significantly narrows the search space of the whole traffic network, and the surrogate-assisted optimizer greatly lowers the computational burden by reducing the number of expensive traffic simulations.

Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation

no code implementations28 Feb 2021 Lie Ju, Xin Wang, Lin Wang, Dwarikanath Mahapatra, Xin Zhao, Mehrtash Harandi, Tom Drummond, Tongliang Liu, ZongYuan Ge

In this paper, we systematically discuss and define the two common types of label noise in medical images - disagreement label noise from inconsistency expert opinions and single-target label noise from wrong diagnosis record.

Benchmarking General Classification +3

STS-GAN: Can We Synthesize Solid Texture with High Fidelity from Arbitrary 2D Exemplar?

no code implementations8 Feb 2021 Xin Zhao, Jifeng Guo, Lin Wang, Fanqi Li, Jiahao Li, Junteng Zheng, Bo Yang

Solid texture synthesis (STS), an effective way to extend a 2D exemplar to a 3D solid volume, exhibits advantages in computational photography.

STS Texture Synthesis

DEFT: Distilling Entangled Factors by Preventing Information Diffusion

no code implementations8 Feb 2021 Jiantao Wu, Lin Wang, Bo Yang, Fanqi Li, Chunxiuzi Liu, Jin Zhou

Disentanglement is a highly desirable property of representation owing to its similarity to human understanding and reasoning.


OPT-GAN: A Broad-Spectrum Global Optimizer for Black-box Problems by Learning Distribution

1 code implementation7 Feb 2021 Minfang Lu, Shuai Ning, Shuangrong Liu, Fengyang Sun, Bo Zhang, Bo Yang, Lin Wang

Black-box optimization (BBO) algorithms are concerned with finding the best solutions for problems with missing analytical details.

An embedded multichannel sound acquisition system for drone audition

no code implementations17 Jan 2021 Michael Clayton, Lin Wang, Andrew McPherson, Andrea Cavallaro

Microphone array techniques can improve the acoustic sensing performance on drones, compared to the use of a single microphone.

Locally symmetric lattices for storage ring light sources

no code implementations5 Jan 2021 Zhenghe Bai, Penghui Yang, Guangyao Feng, Weimin Li, Lin Wang

Two kinds of locally symmetric lattices are designed for a 2. 2 GeV diffraction-limited storage ring to demonstrate the lattice concept.

Accelerator Physics

CDNet: Centripetal Direction Network for Nuclear Instance Segmentation

2 code implementations ICCV 2021 Hongliang He, Zhongyi Huang, Yao Ding, Guoli Song, Lin Wang, Qian Ren, Pengxu Wei, Zhiqiang Gao, Jie Chen

Specifically, we define the centripetal direction feature as a class of adjacent directions pointing to the nuclear center to represent the spatial relationship between pixels within the nucleus.

Instance Segmentation Semantic Segmentation

Operator as a Service: Stateful Serverless Complex Event Processing

1 code implementation9 Dec 2020 Manisha Luthra, Sebastian Hennig, Kamran Razavi, Lin Wang, Boris Koldehofe

In this paper, we propose CEPLESS, a scalable data management system that decouples the specification from the runtime system by building on the principles of serverless computing.

Networking and Internet Architecture Distributed, Parallel, and Cluster Computing

Disentangling Action Sequences: Discovering Correlated Samples

no code implementations17 Oct 2020 Jiantao Wu, Lin Wang

Disentanglement is a highly desirable property of representation due to its similarity with human's understanding and reasoning.


Go viral or go broadcast? Characterizing the virality and growth of cascades

1 code implementation1 Jun 2020 Yafei Zhang, Lin Wang, Jonathan J. H. Zhu, Xiaofan Wang

Quantifying the virality of cascades is an important question across disciplines such as the transmission of disease, the spread of information and the diffusion of innovations.

Physics and Society Social and Information Networks

Dimensionality Reduction for Sentiment Classification: Evolving for the Most Prominent and Separable Features

no code implementations1 Jun 2020 Aftab Anjum, Mazharul Islam, Lin Wang

These techniques reject the features by considering term presence difference for SentiTPC and ratio of the distribution distinction for SentiTPR.

Dimensionality Reduction General Classification +2

A Novel Graphic Bending Transformation on Benchmark

no code implementations21 Apr 2020 Chunxiuzi Liu, Fengyang Sun, Qingrui Ni, Lin Wang, Bo Yang

Classical benchmark problems utilize multiple transformation techniques to increase optimization difficulty, e. g., shift for anti centering effect and rotation for anti dimension sensitivity.

Evolutionary Algorithms

Knowledge Distillation and Student-Teacher Learning for Visual Intelligence: A Review and New Outlooks

2 code implementations13 Apr 2020 Lin Wang, Kuk-Jin Yoon

To achieve faster speeds and to handle the problems caused by the lack of data, knowledge distillation (KD) has been proposed to transfer information learned from one model to another.

Knowledge Distillation Model Compression +1

EventSR: From Asynchronous Events to Image Reconstruction, Restoration, and Super-Resolution via End-to-End Adversarial Learning

1 code implementation CVPR 2020 Lin Wang, Tae-Kyun Kim, Kuk-Jin Yoon

While each phase is mainly for one of the three tasks, the networks in earlier phases are fine-tuned by respective loss functions in an end-to-end manner.

Image Reconstruction Super-Resolution

DSSLP: A Distributed Framework for Semi-supervised Link Prediction

no code implementations27 Feb 2020 Dalong Zhang, Xianzheng Song, Ziqi Liu, Zhiqiang Zhang, Xin Huang, Lin Wang, Jun Zhou

Instead of training model on the whole graph, DSSLP is proposed to train on the \emph{$k$-hops neighborhood} of nodes in a mini-batch setting, which helps reduce the scale of the input graph and distribute the training procedure.

Link Prediction

Deceiving Image-to-Image Translation Networks for Autonomous Driving with Adversarial Perturbations

no code implementations6 Jan 2020 Lin Wang, Wonjune Cho, Kuk-Jin Yoon

However, most previous works have focused on image classification tasks, and it has never been studied regarding adversarial perturbations on Image-to-image (Im2Im) translation tasks, showing great success in handling paired and/or unpaired mapping problems in the field of autonomous driving and robotics.

Autonomous Driving Image Classification +3

Predicting Network Controllability Robustness: A Convolutional Neural Network Approach

no code implementations26 Aug 2019 Yang Lou, Yaodong He, Lin Wang, Guanrong Chen

Under the new framework, a fairly large number of training data generated by simulations are used to train a convolutional neural network for predicting the controllability robustness according to the input network-adjacency matrices, without performing conventional attack simulations.

Improving Neural Network Classifier using Gradient-based Floating Centroid Method

no code implementations21 Jul 2019 Mazharul Islam, Shuangrong Liu, Lin Wang, Xiaojing Zhang

In this study, a gradient-based floating centroid (GDFC) method is introduced to address the fixed centroid problem for the neural network classifiers optimized by gradient-based methods.

A Novel Neural Network-Based Symbolic Regression Method: Neuro-Encoded Expression Programming

no code implementations6 Apr 2019 Aftab Anjum, Fengyang Sun, Lin Wang, Jeff Orchard

Neuro-encoded expression programming(NEEP) that aims to offer a novel continuous representation of combinatorial encoding for genetic programming methods is proposed in this paper.

Evolutionary Algorithms regression +1

Accelerating flux balance calculations in genome-scale metabolic models by localizing the application of loopless constraints

1 code implementation11 Nov 2017 Siu Hung Joshua Chan, Lin Wang, Satyakam Dash, Costas D. Maranas

Background: Genome-scale metabolic network models and constraint-based modeling techniques have become important tools for analyzing cellular metabolism.

Molecular Networks

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