Search Results for author: Chenglong Li

Found 91 papers, 44 papers with code

UGG-ReID: Uncertainty-Guided Graph Model for Multi-Modal Object Re-Identification

no code implementations7 Jul 2025 Xixi Wan, Aihua Zheng, Bo Jiang, Beibei Wang, Chenglong Li, Jin Tang

Experimental results show that the proposed method achieves excellent performance on all datasets and is significantly better than current methods in terms of noise immunity.

Adversarial Semantic and Label Perturbation Attack for Pedestrian Attribute Recognition

2 code implementations29 May 2025 Weizhe Kong, Xiao Wang, Ruichong Gao, Chenglong Li, Yu Zhang, Xing Yang, YaoWei Wang, Jin Tang

To bridge this gap, this paper proposes the first adversarial attack and defense framework for pedestrian attribute recognition.

Adversarial Attack Attribute +1

NEXT: Multi-Grained Mixture of Experts via Text-Modulation for Multi-Modal Object Re-ID

no code implementations26 May 2025 Shihao Li, Chenglong Li, Aihua Zheng, Andong Lu, Jin Tang, Jixin Ma

Specifically, we decouple the recognition problem into semantic and structural expert branches to separately capture modality-specific appearance and intrinsic structure.

Attribute Caption Generation +3

ICPL-ReID: Identity-Conditional Prompt Learning for Multi-Spectral Object Re-Identification

no code implementations23 May 2025 Shihao Li, Chenglong Li, Aihua Zheng, Jin Tang, Bin Luo

Specifically, we first propose the online prompt learning using learnable text prompt as the identity-level semantic center to bridge the identity semantics of different spectra in online manner.

cross-modal alignment Prompt Learning

Collaborative Enhancement Network for Low-quality Multi-spectral Vehicle Re-identification

no code implementations21 Apr 2025 Aihua Zheng, Yongqi Sun, Zi Wang, Chenglong Li, Jin Tang

To address these problems, we propose the Collaborative Enhancement Network (CoEN), which generates a high-quality proxy from all spectra data and leverages it to supervise the selection of primary spectrum and enhance all spectra features in a collaborative manner, for robust multi-spectral vehicle ReID.

All Vehicle Re-Identification

CM3AE: A Unified RGB Frame and Event-Voxel/-Frame Pre-training Framework

1 code implementation17 Apr 2025 Wentao Wu, Xiao Wang, Chenglong Li, Bo Jiang, Jin Tang, Bin Luo, Qi Liu

Event cameras have attracted increasing attention in recent years due to their advantages in high dynamic range, high temporal resolution, low power consumption, and low latency.

Contrastive Learning

Multimodal Spatio-temporal Graph Learning for Alignment-free RGBT Video Object Detection

no code implementations16 Apr 2025 Qishun Wang, Zhengzheng Tu, Chenglong Li, Bo Jiang

Moreover, to fully exploit the temporal cues for RGBT VOD problem, we introduce Hybrid Structured Temporal Modeling (HSTM), which involves a Temporal Sparse Graph Learning Module (T-SGLM) and Temporal Star Block (TSB).

Graph Learning Graph Representation Learning +2

RGB-Event based Pedestrian Attribute Recognition: A Benchmark Dataset and An Asymmetric RWKV Fusion Framework

1 code implementation14 Apr 2025 Xiao Wang, Haiyang Wang, Shiao Wang, Qiang Chen, Jiandong Jin, Haoyu Song, Bo Jiang, Chenglong Li

In this paper, we revisit these issues and propose a novel multi-modal RGB-Event attribute recognition task by drawing inspiration from the advantages of event cameras in low-light, high-speed, and low-power consumption.

Attribute Pedestrian Attribute Recognition

DehazeMamba: SAR-guided Optical Remote Sensing Image Dehazing with Adaptive State Space Model

no code implementations17 Mar 2025 Zhicheng Zhao, Jinquan Yan, Chenglong Li, Xiao Wang, Jin Tang

Optical remote sensing image dehazing presents significant challenges due to its extensive spatial scale and highly non-uniform haze distribution, which traditional single-image dehazing methods struggle to address effectively.

Image Dehazing Semantic Segmentation +1

Towards General Multimodal Visual Tracking

no code implementations14 Mar 2025 Andong Lu, Mai Wen, Jinhu Wang, Yuanzhi Guo, Chenglong Li, Jin Tang, Bin Luo

Despite quad-modal data provides richer information, the differences in information quantity among modalities and the computational burden from four modalities are two challenging issues in fusing four modalities.

Mamba Visual Tracking

Breaking Shallow Limits: Task-Driven Pixel Fusion for Gap-free RGBT Tracking

no code implementations14 Mar 2025 Andong Lu, Yuanzhi Guo, Wanyu Wang, Chenglong Li, Jin Tang, Bin Luo

To break shallow limits, we propose a novel \textbf{T}ask-driven \textbf{P}ixel-level \textbf{F}usion network, named \textbf{TPF}, which unveils the power of pixel-level fusion in RGBT tracking through a progressive learning framework.

Representation Learning Rgb-T Tracking

Large Language Model Guided Progressive Feature Alignment for Multimodal UAV Object Detection

no code implementations10 Mar 2025 Wentao Wu, Chenglong Li, Xiao Wang, Bin Luo, Qi Liu

To address this problem, we propose a Large Language Model (LLM) guided Progressive feature Alignment Network called LPANet, which leverages the semantic features extracted from a large language model to guide the progressive semantic and spatial alignment between modalities for multimodal UAV object detection.

Language Modeling Language Modelling +4

Alignment-Free RGB-T Salient Object Detection: A Large-scale Dataset and Progressive Correlation Network

1 code implementation19 Dec 2024 Kunpeng Wang, Keke Chen, Chenglong Li, Zhengzheng Tu, Bin Luo

Alignment-free RGB-Thermal (RGB-T) salient object detection (SOD) aims to achieve robust performance in complex scenes by directly leveraging the complementary information from unaligned visible-thermal image pairs, without requiring manual alignment.

object-detection Object Detection +1

Dynamic Disentangled Fusion Network for RGBT Tracking

no code implementations11 Dec 2024 Chenglong Li, Tao Wang, Zhaodong Ding, Yun Xiao, Jin Tang

To address the issue that which fusion models should be activated in the tracking process, we design an adaptive aggregation fusion module to integrate all features from attribute-based fusion models in an adaptive manner with a three-stage training algorithm.

Attribute

Text-Guided Coarse-to-Fine Fusion Network for Robust Remote Sensing Visual Question Answering

no code implementations24 Nov 2024 Zhicheng Zhao, Changfu Zhou, Yu Zhang, Chenglong Li, Xiaoliang Ma, Jin Tang

Specifically, we develop a Text-guided Coarse-to-Fine Attention Refinement (CFAR) module to focus on key areas related to the question in complex remote sensing images.

Question Answering Relational Reasoning +1

Guidance Disentanglement Network for Optics-Guided Thermal UAV Image Super-Resolution

1 code implementation27 Oct 2024 Zhicheng Zhao, Juanjuan Gu, Chenglong Li, Chun Wang, Zhongling Huang, Jin Tang

However, single guidance models make it difficult to generate effective guidance features under favorable and adverse conditions in UAV scenarios, thus limiting the performance of OTUAV-SR. To address this issue, we propose a novel Guidance Disentanglement network (GDNet), which disentangles the optical image representation according to typical UAV scenario attributes to form guidance features under both favorable and adverse conditions, for robust OTUAV-SR.

Attribute Disentanglement +3

Breaking Modality Gap in RGBT Tracking: Coupled Knowledge Distillation

1 code implementation15 Oct 2024 Andong Lu, jiacong Zhao, Chenglong Li, Yun Xiao, Bin Luo

To handle this issue, we take original RGB and TIR networks as the teachers, and distill their content knowledge into two student networks respectively by the style-content orthogonal feature decoupling scheme.

Knowledge Distillation Rgb-T Tracking

Adapting Segment Anything Model to Multi-modal Salient Object Detection with Semantic Feature Fusion Guidance

1 code implementation27 Aug 2024 Kunpeng Wang, Danying Lin, Chenglong Li, Zhengzheng Tu, Bin Luo

Then, we feed the extracted multi-modal semantic features into both the SAM image encoder and mask decoder for fine-tuning and prompting, respectively.

Decoder object-detection +4

VFM-Det: Towards High-Performance Vehicle Detection via Large Foundation Models

1 code implementation23 Aug 2024 Wentao Wu, Fanghua Hong, Xiao Wang, Chenglong Li, Jin Tang

In this work, we propose a new vehicle detection paradigm based on a pre-trained foundation vehicle model (VehicleMAE) and a large language model (T5), termed VFM-Det.

Contrastive Learning Language Modelling +3

Pedestrian Attribute Recognition: A New Benchmark Dataset and A Large Language Model Augmented Framework

2 code implementations19 Aug 2024 Jiandong Jin, Xiao Wang, Qian Zhu, Haiyang Wang, Chenglong Li

To address this issue, this paper proposes a new large-scale, cross-domain pedestrian attribute recognition dataset to fill the data gap, termed MSP60K.

Attribute Ensemble Learning +4

RGBT Tracking via All-layer Multimodal Interactions with Progressive Fusion Mamba

no code implementations16 Aug 2024 Andong Lu, Wanyu Wang, Chenglong Li, Jin Tang, Bin Luo

Existing RGBT tracking methods often design various interaction models to perform cross-modal fusion of each layer, but can not execute the feature interactions among all layers, which plays a critical role in robust multimodal representation, due to large computational burden.

All Mamba +2

Cross-modulated Attention Transformer for RGBT Tracking

no code implementations5 Aug 2024 Yun Xiao, jiacong Zhao, Andong Lu, Chenglong Li, Yin Lin, Bing Yin, Cong Liu

Existing Transformer-based RGBT trackers achieve remarkable performance benefits by leveraging self-attention to extract uni-modal features and cross-attention to enhance multi-modal feature interaction and template-search correlation computation.

Rgb-T Tracking

Semantics Guided Disentangled GAN for Chest X-ray Image Rib Segmentation

no code implementations22 Jul 2024 Lili Huang, Dexin Ma, Xiaowei Zhao, Chenglong Li, Haifeng Zhao, Jin Tang, Chuanfu Li

Hence, we propose a novel Semantics guided Disentangled GAN (SD-GAN), which can generate the high-quality training data by fully utilizing the semantic information of different organs, for chest X-ray image rib segmentation.

Generative Adversarial Network Segmentation

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.

Articles Attribute +2

Learning Adaptive Fusion Bank for Multi-modal Salient Object Detection

1 code implementation3 Jun 2024 Kunpeng Wang, Zhengzheng Tu, Chenglong Li, Cheng Zhang, Bin Luo

To adaptively select the appropriate fusion scheme for multi-modal input, we introduce an adaptive ensemble module that forms the adaptive fusion bank, which is embedded into hierarchical layers for sufficient fusion of different source data.

object-detection Object Detection +2

Alignment-Free RGBT Salient Object Detection: Semantics-guided Asymmetric Correlation Network and A Unified Benchmark

1 code implementation3 Jun 2024 Kunpeng Wang, Danying Lin, Chenglong Li, Zhengzheng Tu, Bin Luo

In this paper, we make the first attempt to address RGBT SOD for initially captured RGB and thermal image pairs without manual alignment.

object-detection Object Detection +2

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

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.

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

Transformer RGBT Tracking with Spatio-Temporal Multimodal Tokens

no code implementations3 Jan 2024 Dengdi Sun, Yajie Pan, Andong Lu, Chenglong Li, Bin Luo

We introduce independent dynamic template tokens to interact with the search region, embedding temporal information to address appearance changes, while also retaining the involvement of the initial static template tokens in the joint feature extraction process to ensure the preservation of the original reliable target appearance information that prevent deviations from the target appearance caused by traditional temporal updates.

Rgb-T Tracking Template Matching

Group Multi-View Transformer for 3D Shape Analysis with Spatial Encoding

1 code implementation27 Dec 2023 Lixiang Xu, Qingzhe Cui, Richang Hong, Wei Xu, Enhong Chen, Xin Yuan, Chenglong Li, Yuanyan Tang

The large model GMViT achieves excellent 3D classification and retrieval results on the benchmark datasets ModelNet, ShapeNetCore55, and MCB.

3D Classification 3D Shape Recognition +2

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

1 code implementation25 Dec 2023 Andong Lu, Chenglong Li, Tianrui Zha, Jin Tang, XiaoFeng Wang, Bin Luo

Prevalent nighttime person re-identification (ReID) methods typically combine image relighting and ReID networks in a sequential manner.

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.

Prompt Learning

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

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.

Morphological Profiling for Drug Discovery in the Era of Deep Learning

no code implementations13 Dec 2023 Qiaosi Tang, Ranjala Ratnayake, Gustavo Seabra, Zhe Jiang, Ruogu Fang, Lina Cui, Yousong Ding, Tamer Kahveci, Jiang Bian, Chenglong Li, Hendrik Luesch, Yanjun Li

Additionally, we illuminate the application of morphological profiling in phenotypic drug discovery and highlight potential challenges and opportunities in this field.

Cell Segmentation Deep Learning +3

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

Unified-modal Salient Object Detection via Adaptive Prompt Learning

1 code implementation28 Nov 2023 Kunpeng Wang, Chenglong Li, Zhengzheng Tu, Zhengyi Liu, Bin Luo

Existing single-modal and multi-modal salient object detection (SOD) methods focus on designing specific architectures tailored for their respective tasks.

object-detection Object Detection +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

Erasure-based Interaction Network for RGBT Video Object Detection and A Unified Benchmark

no code implementations3 Aug 2023 Zhengzheng Tu, Qishun Wang, Hongshun Wang, Kunpeng Wang, Chenglong Li

Recently, many breakthroughs are made in the field of Video Object Detection (VOD), but the performance is still limited due to the imaging limitations of RGB sensors in adverse illumination conditions.

object-detection Video Object Detection

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

Flare-Aware Cross-modal Enhancement Network for Multi-spectral Vehicle Re-identification

1 code implementation23 May 2023 Aihua Zheng, Zhiqi Ma, Zi Wang, Chenglong Li

Finally, to evaluate the proposed FACENet in handling intense flare, we introduce a new multi-spectral vehicle re-ID dataset, called WMVEID863, with additional challenges such as motion blur, significant background changes, and particularly intense flare degradation.

Vehicle Re-Identification

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.

Parallel Augmentation and Dual Enhancement for Occluded Person Re-identification

1 code implementation11 Oct 2022 Zi Wang, Huaibo Huang, Aihua Zheng, Chenglong Li, Ran He

To alleviate these two issues, we propose a simple yet effective method with Parallel Augmentation and Dual Enhancement (PADE), which is robust on both occluded and non-occluded data and does not require any auxiliary clues.

Occluded Person Re-Identification

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

Ubiquitous Indoor Fine-Grained Positioning and Tracking: A Channel Response Perspective

no code implementations25 Sep 2022 Chenglong Li, Emmeric Tanghe, Sofie Pollin, Wout Joseph

Then, we present a micro-benchmark of channel response-based direct positioning and tracking for both device-based and contact-free schemes.

Position

Contact-Free Multi-Target Tracking Using Distributed Massive MIMO-OFDM Communication System: Prototype and Analysis

no code implementations23 Aug 2022 Chenglong Li, Sibren De Bast, Yang Miao, Emmeric Tanghe, Sofie Pollin, Wout Joseph

To evade the complex association problem of distributed massive MIMO-based MTT, we propose to use a complex Bayesian compressive sensing (CBCS) algorithm to estimate the targets' locations based on the extracted target-of-interest CSI signal directly.

Compressive Sensing Human Activity Recognition

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

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

Cross-Modal Object Tracking: Modality-Aware Representations and A Unified Benchmark

no code implementations8 Nov 2021 Chenglong Li, Tianhao Zhu, Lei Liu, Xiaonan Si, Zilin Fan, Sulan Zhai

To promote the research and development of cross-modal object tracking, we propose a new algorithm, which learns the modality-aware target representation to mitigate the appearance gap between RGB and NIR modalities in the tracking process.

Object Tracking Visual Tracking

Multi-Static UWB Radar-based Passive Human Tracking Using COTS Devices

1 code implementation27 Sep 2021 Chenglong Li, Emmeric Tanghe, Jaron Fontaine, Luc Martens, Jac Romme, Gaurav Singh, Eli de Poorter, Wout Joseph

Due to its high delay resolution, the ultra-wideband (UWB) technique has been widely adopted for fine-grained indoor localization.

Indoor Localization

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

Towards Fine-Grained Indoor Localization based on Massive MIMO-OFDM System: Experiment and Analysis

no code implementations27 Mar 2021 Chenglong Li, Sibren De Bast, Emmeric Tanghe, Sofie Pollin, Wout Joseph

On top of the available MPCs, we propose a generalized fingerprinting system based on different single-metric and hybrid-metric schemes.

Indoor Localization

Text Analytics for Resilience-Enabled Extreme Events Reconnaissance

no code implementations26 Nov 2020 Alicia Y. Tsai, Selim Gunay, Minjune Hwang, Pengyuan Zhai, Chenglong Li, Laurent El Ghaoui, Khalid M. Mosalam

Post-hazard reconnaissance for natural disasters (e. g., earthquakes) is important for understanding the performance of the built environment, speeding up the recovery, enhancing resilience and making informed decisions related to current and future hazards.

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

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

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

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.

Diversity Thermal Infrared Object Tracking +1

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

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

DeepAtom: A Framework for Protein-Ligand Binding Affinity Prediction

1 code implementation1 Dec 2019 Yanjun Li, Mohammad A. Rezaei, Chenglong Li, Xiaolin Li, Dapeng Wu

The cornerstone of computational drug design is the calculation of binding affinity between two biological counterparts, especially a chemical compound, i. e., a ligand, and a protein.

Drug Design Drug Discovery +3

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

Attributes Guided Feature Learning for Vehicle Re-identification

no code implementations22 May 2019 Hongchao Li, Xianmin Lin, Aihua Zheng, Chenglong Li, Bin Luo, Ran He, Amir Hussain

In particular, our network is end-to-end trained and contains three subnetworks of deep features embedded by the corresponding attributes (i. e., camera view, vehicle type and vehicle color).

Generative Adversarial Network Vehicle Re-Identification

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 +7

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

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

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.

Deep Reinforcement Learning Object +1

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

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

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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