Search Results for author: Jin Tang

Found 96 papers, 44 papers with code

An Empirical Study of Mamba-based Pedestrian Attribute Recognition

1 code implementation15 Jul 2024 Xiao Wang, Weizhe Kong, Jiandong Jin, Shiao Wang, Ruichong Gao, Qingchuan Ma, Chenglong Li, Jin Tang

To further tap into the potential of the novel Mamba architecture for PAR tasks, this paper designs and adapts Mamba into two typical PAR frameworks, i. e., the text-image fusion approach and pure vision Mamba multi-label recognition framework.

Attribute Pedestrian Attribute Recognition

Retain, Blend, and Exchange: A Quality-aware Spatial-Stereo Fusion Approach for Event Stream Recognition

1 code implementation27 Jun 2024 Lan Chen, Dong Li, Xiao Wang, Pengpeng Shao, Wei zhang, YaoWei Wang, Yonghong Tian, Jin Tang

In this paper, we propose a novel dual-stream framework for event stream-based pattern recognition via differentiated fusion, termed EFV++.

Graph Neural Network

Graph Edge Representation via Tensor Product Graph Convolutional Representation

no code implementations21 Jun 2024 Bo Jiang, Sheng Ge, Ziyan Zhang, Beibei Wang, Jin Tang, Bin Luo

However, existing Graph Convolution (GC) operators are mainly defined on adjacency matrix and node features and generally focus on obtaining effective node embeddings which cannot be utilized to address the graphs with (high-dimensional) edge features.

Graph Learning

A Unified Graph Selective Prompt Learning for Graph Neural Networks

no code implementations15 Jun 2024 Bo Jiang, Hao Wu, Ziyan Zhang, Beibei Wang, Jin Tang

The proposed GSPF integrates the prompt learning on both graph node and edge together, which thus provides a unified prompt model for the graph data.

Graph Representation Learning

AFter: Attention-based Fusion Router for RGBT Tracking

1 code implementation4 May 2024 Andong Lu, Wanyu Wang, Chenglong Li, Jin Tang, Bin Luo

In particular, we design a fusion structure space based on the hierarchical attention network, each attention-based fusion unit corresponding to a fusion operation and a combination of these attention units corresponding to a fusion structure.

Neural Architecture Search Rgb-T Tracking

Pre-training on High Definition X-ray Images: An Experimental Study

1 code implementation27 Apr 2024 Xiao Wang, Yuehang Li, Wentao Wu, Jiandong Jin, Yao Rong, Bo Jiang, Chuanfu Li, Jin Tang

Existing X-ray based pre-trained vision models are usually conducted on a relatively small-scale dataset (less than 500k samples) with limited resolution (e. g., 224 $\times$ 224).

Decoder Miscellaneous

State Space Model for New-Generation Network Alternative to Transformers: A Survey

1 code implementation15 Apr 2024 Xiao Wang, Shiao Wang, Yuhe Ding, Yuehang Li, Wentao Wu, Yao Rong, Weizhe Kong, Ju Huang, Shihao Li, Haoxiang Yang, Ziwen Wang, Bo Jiang, Chenglong Li, YaoWei Wang, Yonghong Tian, Jin Tang

In this paper, we give the first comprehensive review of these works and also provide experimental comparisons and analysis to better demonstrate the features and advantages of SSM.

Long-term Frame-Event Visual Tracking: Benchmark Dataset and Baseline

4 code implementations9 Mar 2024 Xiao Wang, Ju Huang, Shiao Wang, Chuanming Tang, Bo Jiang, Yonghong Tian, Jin Tang, Bin Luo

Current event-/frame-event based trackers undergo evaluation on short-term tracking datasets, however, the tracking of real-world scenarios involves long-term tracking, and the performance of existing tracking algorithms in these scenarios remains unclear.

Object Tracking Rgb-T Tracking

Uncertainty-aware Bridge based Mobile-Former Network for Event-based Pattern Recognition

1 code implementation20 Jan 2024 Haoxiang Yang, Chengguo Yuan, Yabin Zhu, Lan Chen, Xiao Wang, Jin Tang

The mainstream human activity recognition (HAR) algorithms are developed based on RGB cameras, which are easily influenced by low-quality images (e. g., low illumination, motion blur).

Human Activity Recognition

Unifying Graph Contrastive Learning via Graph Message Augmentation

no code implementations8 Jan 2024 Ziyan Zhang, Bo Jiang, Jin Tang, Bin Luo

Based on the proposed GMA, we then propose a unified graph contrastive learning, termed Graph Message Contrastive Learning (GMCL), that employs attribution-guided universal GMA for graph contrastive learning.

Contrastive Learning Data Augmentation +2

CRSOT: Cross-Resolution Object Tracking using Unaligned Frame and Event Cameras

1 code implementation5 Jan 2024 Yabin Zhu, Xiao Wang, Chenglong Li, Bo Jiang, Lin Zhu, Zhixiang Huang, Yonghong Tian, Jin Tang

In this work, we formally propose the task of object tracking using unaligned neuromorphic and visible cameras.

Object Tracking

Nighttime Person Re-Identification via Collaborative Enhancement Network with Multi-domain Learning

no code implementations25 Dec 2023 Andong Lu, Tianrui Zha, Chenglong Li, Jin Tang, XiaoFeng Wang, Bin Luo

To perform effective collaborative modeling between image relighting and person ReID tasks, we integrate the multilevel feature interactions in CENet.

Image Relighting Person Re-Identification

Modality-missing RGBT Tracking: Invertible Prompt Learning and High-quality Benchmarks

1 code implementation25 Dec 2023 Andong Lu, jiacong Zhao, Chenglong Li, Jin Tang, Bin Luo

To address this challenge, we propose a novel invertible prompt learning approach, which integrates the content-preserving prompts into a well-trained tracking model to adapt to various modality-missing scenarios, for robust RGBT tracking.

Prototype-based Cross-Modal Object Tracking

1 code implementation22 Dec 2023 Lei Liu, Chenglong Li, Futian Wang, Longfeng Shen, Jin Tang

In particular, we design a multi-modal prototype to represent target information by multi-kind samples, including a fixed sample from the first frame and two representative samples from different modalities.

Object Object Tracking

Cross-Modal Object Tracking via Modality-Aware Fusion Network and A Large-Scale Dataset

1 code implementation22 Dec 2023 Lei Liu, Mengya Zhang, Cheng Li, Chenglong Li, Jin Tang

Visual tracking often faces challenges such as invalid targets and decreased performance in low-light conditions when relying solely on RGB image sequences.

Object Tracking Visual Tracking

Cross-Covariate Gait Recognition: A Benchmark

1 code implementation22 Dec 2023 Shinan Zou, Chao Fan, Jianbo Xiong, Chuanfu Shen, Shiqi Yu, Jin Tang

Compared to existing datasets, CCGR has both population and individual-level diversity.

Diversity Gait Recognition

A Multi-Stage Adaptive Feature Fusion Neural Network for Multimodal Gait Recognition

1 code implementation22 Dec 2023 Shinan Zou, Jianbo Xiong, Chao Fan, Shiqi Yu, Jin Tang

In this paper, by considering the temporal and spatial characteristics of gait data, we propose a multi-stage feature fusion strategy (MSFFS), which performs multimodal fusions at different stages in the feature extraction process.

Gait Recognition

Unleashing the Power of CNN and Transformer for Balanced RGB-Event Video Recognition

1 code implementation18 Dec 2023 Xiao Wang, Yao Rong, Shiao Wang, Yuan Chen, Zhe Wu, Bo Jiang, Yonghong Tian, Jin Tang

It is intuitive to combine them for high-performance RGB-Event based video recognition, however, existing works fail to achieve a good balance between the accuracy and model parameters, as shown in Fig.~\ref{firstimage}.

Video Recognition

Pedestrian Attribute Recognition via CLIP based Prompt Vision-Language Fusion

2 code implementations17 Dec 2023 Xiao Wang, Jiandong Jin, Chenglong Li, Jin Tang, Cheng Zhang, Wei Wang

In this paper, we formulate PAR as a vision-language fusion problem and fully exploit the relations between pedestrian images and attribute labels.

Attribute Contrastive Learning +2

Structural Information Guided Multimodal Pre-training for Vehicle-centric Perception

1 code implementation15 Dec 2023 Xiao Wang, Wentao Wu, Chenglong Li, Zhicheng Zhao, Zhe Chen, Yukai Shi, Jin Tang

To address this issue, we propose a novel vehicle-centric pre-training framework called VehicleMAE, which incorporates the structural information including the spatial structure from vehicle profile information and the semantic structure from informative high-level natural language descriptions for effective masked vehicle appearance reconstruction.

SequencePAR: Understanding Pedestrian Attributes via A Sequence Generation Paradigm

2 code implementations4 Dec 2023 Jiandong Jin, Xiao Wang, Chenglong Li, Lili Huang, Jin Tang

Then, a Transformer decoder is proposed to generate the human attributes by incorporating the visual features and attribute query tokens.

Attribute Decoder +2

Illumination Distillation Framework for Nighttime Person Re-Identification and A New Benchmark

1 code implementation31 Aug 2023 Andong Lu, Zhang Zhang, Yan Huang, Yifan Zhang, Chenglong Li, Jin Tang, Liang Wang

The illumination enhancement branch first estimates an enhanced image from the nighttime image using a nonlinear curve mapping method and then extracts the enhanced features.

Person Re-Identification

SSTFormer: Bridging Spiking Neural Network and Memory Support Transformer for Frame-Event based Recognition

1 code implementation8 Aug 2023 Xiao Wang, Zongzhen Wu, Yao Rong, Lin Zhu, Bo Jiang, Jin Tang, Yonghong Tian

Secondly, they adopt either Spiking Neural Networks (SNN) for energy-efficient recognition with suboptimal results, or Artificial Neural Networks (ANN) for energy-intensive, high-performance recognition.

Point-Voxel Absorbing Graph Representation Learning for Event Stream based Recognition

1 code implementation8 Jun 2023 Bo Jiang, Chengguo Yuan, Xiao Wang, Zhimin Bao, Lin Zhu, Yonghong Tian, Jin Tang

To address these issues, we propose a novel dual point-voxel absorbing graph representation learning for event stream data representation.

Event data classification Graph Representation Learning

AMatFormer: Efficient Feature Matching via Anchor Matching Transformer

no code implementations30 May 2023 Bo Jiang, Shuxian Luo, Xiao Wang, Chuanfu Li, Jin Tang

Second, AMatFormer adopts a shared FFN module to further embed the features of two images into the common domain and thus learn the consensus feature representations for the matching problem.

Multi-query Vehicle Re-identification: Viewpoint-conditioned Network, Unified Dataset and New Metric

no code implementations25 May 2023 Aihua Zheng, Chaobin Zhang, Weijun Zhang, Chenglong Li, Jin Tang, Chang Tan, Ruoran Jia

Existing vehicle re-identification methods mainly rely on the single query, which has limited information for vehicle representation and thus significantly hinders the performance of vehicle Re-ID in complicated surveillance networks.

Scene Recognition Vehicle Re-Identification

AGFormer: Efficient Graph Representation with Anchor-Graph Transformer

no code implementations12 May 2023 Bo Jiang, Fei Xu, Ziyan Zhang, Jin Tang, Feiping Nie

To alleviate the local receptive issue of GCN, Transformers have been exploited to capture the long range dependences of nodes for graph data representation and learning.

RGBT Tracking via Progressive Fusion Transformer with Dynamically Guided Learning

no code implementations26 Mar 2023 Yabin Zhu, Chenglong Li, Xiao Wang, Jin Tang, Zhixiang Huang

In addition, existing learning methods of RGBT trackers either fuse multimodal features into one for final classification, or exploit the relationship between unimodal branches and fused branch through a competitive learning strategy.

An end-to-end multi-scale network for action prediction in videos

no code implementations31 Dec 2022 Xiaofa Liu, Jianqin Yin, Yuan Sun, Zhicheng Zhang, Jin Tang

Unlike most existing methods with offline feature generation, our method directly takes frames as input and further models motion evolution on two different temporal scales. Therefore, we solve the complexity problems of the two stages of modeling and the problem of insufficient temporal and spatial information of a single scale.

Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-Experts

1 code implementation8 Oct 2022 Tao Zhong, Zhixiang Chi, Li Gu, Yang Wang, Yuanhao Yu, Jin Tang

Most existing methods perform training on multiple source domains using a single model, and the same trained model is used on all unseen target domains.

Domain Generalization Knowledge Distillation +3

Hand Hygiene Assessment via Joint Step Segmentation and Key Action Scorer

no code implementations25 Sep 2022 Chenglong Li, Qiwen Zhu, Tubiao Liu, Jin Tang, Yu Su

To address this issue, we design a multi-stage convolution-transformer network for step segmentation.

Action Assessment Segmentation

Detecting Rotated Objects as Gaussian Distributions and Its 3-D Generalization

1 code implementation22 Sep 2022 Xue Yang, Gefan Zhang, Xiaojiang Yang, Yue Zhou, Wentao Wang, Jin Tang, Tao He, Junchi Yan

Existing detection methods commonly use a parameterized bounding box (BBox) to model and detect (horizontal) objects and an additional rotation angle parameter is used for rotated objects.


Multi-spectral Vehicle Re-identification with Cross-directional Consistency Network and a High-quality Benchmark

1 code implementation1 Aug 2022 Aihua Zheng, Xianpeng Zhu, Zhiqi Ma, Chenglong Li, Jin Tang, Jixin Ma

In particular, we design a new cross-directional center loss to pull the modality centers of each identity close to mitigate cross-modality discrepancy, while the sample centers of each identity close to alleviate the sample discrepancy.

Vehicle Re-Identification

Disentangled Generation Network for Enlarged License Plate Recognition and A Unified Dataset

no code implementations2 Jun 2022 Chenglong Li, Xiaobin Yang, Guohao Wang, Aihua Zheng, Chang Tan, Ruoran Jia, Jin Tang

License plate recognition plays a critical role in many practical applications, but license plates of large vehicles are difficult to be recognized due to the factors of low resolution, contamination, low illumination, and occlusion, to name a few.

Disentanglement Diversity +3

Beyond Greedy Search: Tracking by Multi-Agent Reinforcement Learning-based Beam Search

1 code implementation19 May 2022 Xiao Wang, Zhe Chen, Bo Jiang, Jin Tang, Bin Luo, DaCheng Tao

To track the target in a video, current visual trackers usually adopt greedy search for target object localization in each frame, that is, the candidate region with the maximum response score will be selected as the tracking result of each frame.

Decision Making Image Captioning +5

Tiny Object Tracking: A Large-scale Dataset and A Baseline

1 code implementation11 Feb 2022 Yabin Zhu, Chenglong Li, Yao Liu, Xiao Wang, Jin Tang, Bin Luo, Zhixiang Huang

Tiny objects, frequently appearing in practical applications, have weak appearance and features, and receive increasing interests in meany vision tasks, such as object detection and segmentation.

Attribute Knowledge Distillation +4

Attribute-Based Progressive Fusion Network for RGBT Tracking

2 code implementations AAAI2022 2022 Yun Xiao, Mengmeng Yang, Chenglong Li, Lei Liu, Jin Tang

RGBT tracking usually suffers from various challenging factors of fast motion, scale variation, illumination variation, thermal crossover and occlusion, to name a few.

Attribute Rgb-T Tracking

MetaFSCIL: A Meta-Learning Approach for Few-Shot Class Incremental Learning

no code implementations CVPR 2022 Zhixiang Chi, Li Gu, Huan Liu, Yang Wang, Yuanhao Yu, Jin Tang

The learning objective of these methods is often hand-engineered and is not directly tied to the objective (i. e. incrementally learning new classes) during testing.

Few-Shot Class-Incremental Learning Incremental Learning +1

GAMnet: Robust Feature Matching via Graph Adversarial-Matching Network

no code implementations MM 2021 Bo Jiang, Pengfei Sun, Ziyan Zhang, Jin Tang, Bin Luo

Also, GAMnet exploits sparse GM optimization as correspondence solver which is differentiable and can also incorporate discrete one-to-one matching constraints approximately in natural in the final matching prediction.

Ranked #8 on Graph Matching on PASCAL VOC (matching accuracy metric)

Graph Matching

Test-Time Fast Adaptation for Dynamic Scene Deblurring via Meta-Auxiliary Learning

no code implementations CVPR 2021 Zhixiang Chi, Yang Wang, Yuanhao Yu, Jin Tang

Therefore, we are able to exploit the internal information at test time via the auxiliary task to enhance the performance of deblurring.

Auxiliary Learning Deblurring +1

Tracking by Joint Local and Global Search: A Target-aware Attention based Approach

1 code implementation9 Jun 2021 Xiao Wang, Jin Tang, Bin Luo, YaoWei Wang, Yonghong Tian, Feng Wu

In this paper, we propose a novel and general target-aware attention mechanism (termed TANet) and integrate it with tracking-by-detection framework to conduct joint local and global search for robust tracking.

Decoder Object +1

LasHeR: A Large-scale High-diversity Benchmark for RGBT Tracking

1 code implementation27 Apr 2021 Chenglong Li, Wanlin Xue, Yaqing Jia, Zhichen Qu, Bin Luo, Jin Tang, Dengdi Sun

RGBT tracking receives a surge of interest in the computer vision community, but this research field lacks a large-scale and high-diversity benchmark dataset, which is essential for both the training of deep RGBT trackers and the comprehensive evaluation of RGBT tracking methods.

Diversity Rgb-T Tracking +1

Temporal Consistency Two-Stream CNN for Human Motion Prediction

no code implementations11 Apr 2021 Jin Tang, Jin Zhang, Jianqin Yin

In this paper, we propose a novel temporal fusion (TF) module to fuse the two-stream joints' information to predict human motion, including a temporal concatenation and a reinforcement trajectory spatial-temporal (TST) block, specifically designed to keep prediction temporal consistency.

Human motion prediction motion prediction +2

Dynamic Attention guided Multi-Trajectory Analysis for Single Object Tracking

1 code implementation30 Mar 2021 Xiao Wang, Zhe Chen, Jin Tang, Bin Luo, YaoWei Wang, Yonghong Tian, Feng Wu

In this paper, we propose to introduce more dynamics by devising a dynamic attention-guided multi-trajectory tracking strategy.

Object Tracking

PICA: A Pixel Correlation-based Attentional Black-box Adversarial Attack

no code implementations19 Jan 2021 Jie Wang, Zhaoxia Yin, Jin Tang, Jing Jiang, Bin Luo

The studies on black-box adversarial attacks have become increasingly prevalent due to the intractable acquisition of the structural knowledge of deep neural networks (DNNs).

Adversarial Attack

Image Enhancement using Fuzzy Intensity Measure and Adaptive Clipping Histogram Equalization

no code implementations15 Jan 2021 Xiangyuan Zhu, Xiaoming Xiao, Tardi Tjahjadi, Zhihu Wu, Jin Tang

Image enhancement aims at processing an input image so that the visual content of the output image is more pleasing or more useful for certain applications.

Image Enhancement

Viewpoint-aware Progressive Clustering for Unsupervised Vehicle Re-identification

no code implementations18 Nov 2020 Aihua Zheng, Xia Sun, Chenglong Li, Jin Tang

Comprehensive experiments against the state-of-the-art methods on two multi-viewpoint benchmark datasets VeRi and VeRi-Wild validate the promising performance of the proposed method in both with and without domain adaption scenarios while handling unsupervised vehicle Re-ID.

Clustering Domain Adaptation +2

Duality-Gated Mutual Condition Network for RGBT Tracking

no code implementations14 Nov 2020 Andong Lu, Cun Qian, Chenglong Li, Jin Tang, Liang Wang

To deal with the tracking failure caused by sudden camera motion, which often occurs in RGBT tracking, we design a resampling strategy based on optical flow algorithms.

Optical Flow Estimation Rgb-T Tracking

RGBT Tracking via Multi-Adapter Network with Hierarchical Divergence Loss

no code implementations14 Nov 2020 Andong Lu, Chenglong Li, Yuqing Yan, Jin Tang, Bin Luo

In specific, we use the modified VGG-M as the generality adapter to extract the modality-shared target representations. To extract the modality-specific features while reducing the computational complexity, we design a modality adapter, which adds a small block to the generality adapter in each layer and each modality in a parallel manner.

Representation Learning Rgb-T Tracking

Challenge-Aware RGBT Tracking

no code implementations ECCV 2020 Chenglong Li, Lei Liu, Andong Lu, Qing Ji, Jin Tang

RGB and thermal source data suffer from both shared and specific challenges, and how to explore and exploit them plays a critical role to represent the target appearance in RGBT tracking.

Rgb-T Tracking

All at Once: Temporally Adaptive Multi-Frame Interpolation with Advanced Motion Modeling

no code implementations ECCV 2020 Zhixiang Chi, Rasoul Mohammadi Nasiri, Zheng Liu, Juwei Lu, Jin Tang, Konstantinos N. Plataniotis

Recent advances in high refresh rate displays as well as the increased interest in high rate of slow motion and frame up-conversion fuel the demand for efficient and cost-effective multi-frame video interpolation solutions.

Multi-interactive Encoder-decoder Network for RGBT Salient Object Detection

2 code implementations5 Jun 2020 Zhengzheng Tu, Zhun Li, Chenglong Li, Yang Lang, Jin Tang

RGBT salient object detection (SOD) aims to segment the common prominent regions of visible and thermal infrared images.

Decoder object-detection +2

Multi-interactive Dual-decoder for RGB-thermal Salient Object Detection

2 code implementations5 May 2020 Zhengzheng Tu, Zhun Li, Chenglong Li, Yang Lang, Jin Tang

Then, we design a novel dual-decoder to conduct the interactions of multi-level features, two modalities and global contexts.

Decoder object-detection +2

M$^5$L: Multi-Modal Multi-Margin Metric Learning for RGBT Tracking

no code implementations17 Mar 2020 Zhengzheng Tu, Chun Lin, Chenglong Li, Jin Tang, Bin Luo

Classifying the confusing samples in the course of RGBT tracking is a quite challenging problem, which hasn't got satisfied solution.

Metric Learning

FMT:Fusing Multi-task Convolutional Neural Network for Person Search

no code implementations1 Mar 2020 Sulan Zhai, Shunqiang Liu, Xiao Wang, Jin Tang

Person search is to detect all persons and identify the query persons from detected persons in the image without proposals and bounding boxes, which is different from person re-identification.

Human Detection Person Re-Identification +2

\emph{cm}SalGAN: RGB-D Salient Object Detection with Cross-View Generative Adversarial Networks

1 code implementation21 Dec 2019 Bo Jiang, Zitai Zhou, Xiao Wang, Jin Tang, Bin Luo

Fusing complementary information of RGB and depth has been demonstrated to be effective for image salient object detection which is known as RGB-D salient object detection problem.

Edge Detection Generative Adversarial Network +6

AttKGCN: Attribute Knowledge Graph Convolutional Network for Person Re-identification

no code implementations24 Nov 2019 Bo Jiang, Xixi Wang, Jin Tang

Discriminative feature representation of person image is important for person re-identification (Re-ID) task.

Attribute Person Re-Identification

GLMNet: Graph Learning-Matching Networks for Feature Matching

no code implementations18 Nov 2019 Bo Jiang, Pengfei Sun, Jin Tang, Bin Luo

However, the matching graphs we feed to existing graph convolutional matching networks are generally fixed and independent of graph matching, which thus are not guaranteed to be optimal for the graph matching task.

Graph Learning Graph Matching +1

Context-Aware Graph Attention Networks

no code implementations4 Sep 2019 Bo Jiang, Leiling Wang, Jin Tang, Bin Luo

In particular, CaGAT conducts context-aware learning on both node feature representation and edge (weight) representation simultaneously and cooperatively in a unified manner which can boost their respective performance in network training.

Graph Attention

GmCN: Graph Mask Convolutional Network

no code implementations4 Sep 2019 Bo Jiang, Beibei Wang, Jin Tang, Bin Luo

Graph Convolutional Networks (GCNs) have shown very powerful for graph data representation and learning tasks.

Graph Learning

Semi-supervised Learning with Adaptive Neighborhood Graph Propagation Network

no code implementations14 Aug 2019 Bo Jiang, Leiling Wang, Jin Tang, Bin Luo

In this paper, we first re-interpret graph convolution operation in GCNs as a composition of feature propagation and (non-linear) transformation.

graph construction

Learning Target-oriented Dual Attention for Robust RGB-T Tracking

no code implementations12 Aug 2019 Rui Yang, Yabin Zhu, Xiao Wang, Chenglong Li, Jin Tang

RGB-Thermal object tracking attempt to locate target object using complementary visual and thermal infrared data.

Object Object Tracking +2

Edge-guided Non-local Fully Convolutional Network for Salient Object Detection

no code implementations7 Aug 2019 Zhengzheng Tu, Yan Ma, Chenglong Li, Jin Tang, Bin Luo

To maintain the clear edge structure of salient objects, we propose a novel Edge-guided Non-local FCN (ENFNet) to perform edge guided feature learning for accurate salient object detection.

object-detection RGB Salient Object Detection +1

Learning Compact Target-Oriented Feature Representations for Visual Tracking

no code implementations5 Aug 2019 Chenglong Li, Yan Huang, Liang Wang, Jin Tang, Liang Lin

Many state-of-the-art trackers usually resort to the pretrained convolutional neural network (CNN) model for correlation filtering, in which deep features could usually be redundant, noisy and less discriminative for some certain instances, and the tracking performance might thus be affected.

Visual Tracking

Dense Feature Aggregation and Pruning for RGBT Tracking

no code implementations24 Jul 2019 Yabin Zhu, Chenglong Li, Bin Luo, Jin Tang, Xiao Wang

In different modalities, we propose to prune the densely aggregated features of all modalities in a collaborative way.

Multi-Adapter RGBT Tracking

no code implementations17 Jul 2019 Chenglong Li, Andong Lu, Aihua Zheng, Zhengzheng Tu, Jin Tang

In a specific, the generality adapter is to extract shared object representations, the modality adapter aims at encoding modality-specific information to deploy their complementary advantages, and the instance adapter is to model the appearance properties and temporal variations of a certain object.

Visual Tracking

Improved Hard Example Mining by Discovering Attribute-based Hard Person Identity

no code implementations6 May 2019 Xiao Wang, Ziliang Chen, Rui Yang, Bin Luo, Jin Tang

In this paper, we propose Hard Person Identity Mining (HPIM) that attempts to refine the hard example mining to improve the exploration efficacy in person re-identification.

Attribute Metric Learning +1

Pedestrian Attribute Recognition: A Survey

1 code implementation22 Jan 2019 Xiao Wang, Shaofei Zheng, Rui Yang, Aihua Zheng, Zhe Chen, Jin Tang, Bin Luo

We also review some popular network architectures which have been widely applied in the deep learning community.

Attribute Multi-Label Learning +2

Multiple Graph Adversarial Learning

no code implementations22 Jan 2019 Bo Jiang, Ziyan Zhang, Jin Tang, Bin Luo

In this paper, we propose a novel Multiple Graph Adversarial Learning (MGAL) framework for multi-graph representation and learning.

Quality-Aware Multimodal Saliency Detection via Deep Reinforcement Learning

no code implementations27 Nov 2018 Xiao Wang, Tao Sun, Rui Yang, Chenglong Li, Bin Luo, Jin Tang

In this paper, we propose an efficient quality-aware deep neural network to model the weight of data from each domain using deep reinforcement learning (DRL).

Decision Making Decoder +6

Describe and Attend to Track: Learning Natural Language guided Structural Representation and Visual Attention for Object Tracking

no code implementations25 Nov 2018 Xiao Wang, Chenglong Li, Rui Yang, Tianzhu Zhang, Jin Tang, Bin Luo

To refine the states of the target and re-track the target when it is back to view from heavy occlusion and out of view, we elaborately design a novel subnetwork to learn the target-driven visual attentions from the guidance of both visual and natural language cues.

Object Tracking

Graph Learning-Convolutional Networks

no code implementations25 Nov 2018 Bo Jiang, Ziyan Zhang, Doudou Lin, Jin Tang

Recently, graph Convolutional Neural Networks (graph CNNs) have been widely used for graph data representation and semi-supervised learning tasks.

graph construction Graph Learning

FANet: Quality-Aware Feature Aggregation Network for Robust RGB-T Tracking

no code implementations24 Nov 2018 Yabin Zhu, Chenglong Li, Bin Luo, Jin Tang

This paper investigates how to perform robust visual tracking in adverse and challenging conditions using complementary visual and thermal infrared data (RGBT tracking).

Rgb-T Tracking

Graph Diffusion-Embedding Networks

no code implementations1 Oct 2018 Bo Jiang, Doudou Lin, Jin Tang

We present a novel graph diffusion-embedding networks (GDEN) for graph structured data.

SINT++: Robust Visual Tracking via Adversarial Positive Instance Generation

no code implementations CVPR 2018 Xiao Wang, Chenglong Li, Bin Luo, Jin Tang

Based on the generated hard positive samples, we train a Siamese network for visual tracking and our experiments validate the effectiveness of the introduced algorithm.

Object Visual Tracking

RGB-T Object Tracking:Benchmark and Baseline

no code implementations23 May 2018 Chenglong Li, Xinyan Liang, Yijuan Lu, Nan Zhao, Jin Tang

RGB-Thermal (RGB-T) object tracking receives more and more attention due to the strongly complementary benefits of thermal information to visible data.

8k Object +2

Temporal Coherent and Graph Optimized Manifold Ranking for Visual Tracking

no code implementations17 Apr 2018 Bo Jiang, Doudou Lin, Bin Luo, Jin Tang

To address this problem, we propose a novel unified temporal coherence and graph optimized ranking model for weighted patch representation in visual tracking problem.

Graph Ranking Visual Tracking

Graph Matching via Multiplicative Update Algorithm

no code implementations NeurIPS 2017 Bo Jiang, Jin Tang, Chris Ding, Yihong Gong, Bin Luo

As a fundamental problem in computer vision, graph matching problem can usually be formulated as a Quadratic Programming (QP) problem with doubly stochastic and discrete (integer) constraints.

Graph Matching

Visual Tracking via Dynamic Graph Learning

no code implementations4 Oct 2017 Chenglong Li, Liang Lin, WangMeng Zuo, Jin Tang, Ming-Hsuan Yang

First, the graph is initialized by assigning binary weights of some image patches to indicate the object and background patches according to the predicted bounding box.

Graph Learning Object +2

Binary Constraint Preserving Graph Matching

no code implementations CVPR 2017 Bo Jiang, Jin Tang, Chris Ding, Bin Luo

There are three main contributions of the proposed method: (1) we propose a new graph matching relaxation model, called Binary Constraint Preserving Graph Matching (BPGM), which aims to incorporate the discrete binary mapping constraints more in graph matching relaxation.

Graph Matching

A Unified RGB-T Saliency Detection Benchmark: Dataset, Baselines, Analysis and A Novel Approach

1 code implementation11 Jan 2017 Chenglong Li, Guizhao Wang, Yunpeng Ma, Aihua Zheng, Bin Luo, Jin Tang

In particular, we introduce a weight for each modality to describe the reliability, and integrate them into the graph-based manifold ranking algorithm to achieve adaptive fusion of different source data.

Saliency Detection

SOLD: Sub-Optimal Low-rank Decomposition for Efficient Video Segmentation

no code implementations CVPR 2015 Chenglong Li, Liang Lin, WangMeng Zuo, Shuicheng Yan, Jin Tang

In particular, the affinity matrix with the rank fixed can be decomposed into two sub-matrices of low rank, and then we iteratively optimize them with closed-form solutions.

Video Segmentation Video Semantic Segmentation

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