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A collection of deep learning based RGB-T-Fusion methods, codes, and datasets. The main directions involved are Multispectral Pedestrian Detection, RGB-T Aerial Object Detection, RGB-T Semantic Segmentation, RGB-T Crowd Counting, RGB-T Fusion Tracking.

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Awesome RGB-T Fusion Awesome -RGBT-red

A collection of deep learning based RGB-T-Fusion methods, codes, and datasets.
The main directions involved are Multispectral Pedestrian Detection, RGB-T Aerial Object Detection, RGB-T Semantic Segmentation, RGB-T Salient Object Detection, RGB-T Crowd Counting, RGB-T Fusion Tracking.

Welcome to add valuable papers and codes, feel free to star and contact me. Keep updating....🚀

🔥 News

  • [10/2026]: We have updated this repository with new papers accepted at prestigious conferences.
  • Contents

    1. Multispectral Pedestrian Detection
    2. RGB-T Aerial Object Detection
    3. RGB-T Semantic Segmentation
    4. RGB-T Salient Object Detection
    5. RGB-T Crowd Counting
    6. RGB-T Fusion Tracking

    Multispectral Pedestrian Detection

    Datasets and Tools

    Dataset Years Modality Images Classes
    KAIST 2015 RGB, LWIR 95K 1
    CVC-14 2016 RGB, LWIR 8K 1
    FLIR 2018 RGB, LWIR 20K 5
    FLIR-aligned 2020 RGB, LWIR 5K 3
    Utokyo 2017 RGB, NIR, MIR, FIR 7K 5
    LLVIP 2021 RGB, LWIR 15K 1
    M3FD 2022 RGB, LWIR 4K 6
    Multi-Spectral Stereo 2023 RGB, NIR, LWIR 195K 4
    SMOD 2024 RGB, LWIR 8K 4
    MMPD 2024 RGB, LWIR 260K 1
    InfraParis 2024 RGB, LWIR, Depth 7K 19
    MFAD 2025 RGB, LWIR 12K 6
    MMVIP 2026 RGB, LWIR 128K 2
    RGBT-Ground 2026 RGB, LWIR 40K 5

    KAIST Tools

    • Improved KAIST Testing Annotations provided by Liu et al.download
    • Sanitized KAIST Training Annotations provided by Li et al.download
    • Improved KAIST Training Annotations provided by Zhang et al.download
    • Evalutaion codes.download
    • Annotation: vbb format->xml format.download
    • Evaluation Website.

    Papers

    Vision-Language Model Perception

    1. MLLM Makes Strong Backbone for Multi-Modal Object Detection, Neurips 2026, Yifeng Yang et al., [PDF]
    2. Does Seeing More Mean Knowing More? Mono-Anchored Advantage Normalization for Multi-Source Visual Reasoning, Neurips 2026, Fanhu Zeng et al., [PDF][Code]
    3. RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios, ECCV 2026, Tianyi Zhao et al., [PDF][Code]

    Pretrained Generalist Model

    1. LoME: LoRA-Driven Multimodal Extractor for RGB-X Vision Tasks, TCSVT 2026, Yusi Zhang et al., [PDF][Code]
    2. M-SpecGene: Generalized Foundation Model for RGBT Multispectral Vision, ICCV 2025, Kailai Zhou et al., [PDF][Code]
    3. UniRGB-IR: A Unified Framework for Visible-Infrared Downstream Tasks via Adapter Tuning, ACM MM 2025, Maoxun Yuan et al., [PDF][Code]
    4. When Pedestrian Detection Meets Multi-Modal Learning: Generalist Model and Benchmark Dataset, ECCV 2024, Yi Zhang et al., [PDF][Code]
    5. Mixed Patch Visible-Infrared Modality Agnostic Object Detection, WACV 2025, Heitor R. Medeiros et al., [PDF][Code]

    Modality Bias

    1. AIR-Det: Asymmetric Multimodal Object Detection via Main-Conditioned Residual Learning, ACMMM2026, Ziang Gan et al., [PDF]
    2. Distribution-Aligned Multimodal Fusion for Robust Object Detection, CVPR 2026, Xiaohui Hao et al., [PDF]
    3. UniRGB-IR: A Unified Framework for Visible-Infrared Downstream Tasks via Adapter Tuning, ACM MM 2025, Maoxun Yuan et al., [PDF][Code]
    4. Modality Translation for Object Detection Adaptation Without Forgetting Prior Knowledge, ECCV 2024, Medeiros, Heitor Rapela et al., [PDF][Code]
    5. AMFD: Distillation via Adaptive Multimodal Fusion for Multispectral Pedestrian Detection, Arxiv 2024, Zizhao Chen et al., [PDF][Code]
    6. D3T: Distinctive Dual-Domain Teacher Zigzagging Across RGB-Thermal Gap for Domain-Adaptive Object Detection, CVPR 2024, Dinh Phat Do et al., [PDF][Code]
    7. Causal Mode Multiplexer: A Novel Framework for Unbiased Multispectral Pedestrian Detection, CVPR 2024, Taeheon Kim et al. [PDF][Code]
    8. HalluciDet: Hallucinating RGB Modality for Person Detection Through Privileged Information, WACV 2024, Medeiros, Heitor Rapela et al., [PDF][Code]
    9. Unsupervised Domain Adaptation for Multispectral Pedestrian Detection, CVPR 2019 Workshop , Dayan Guan et al.[PDF][Code]
    10. Pedestrian detection with unsupervised multispectral feature learning using deep neural networks, Information Fusion 2019, Y. Cao et al. Information Fusion 2019, [PDF][Code]
    11. Learning crossmodal deep representations for robust pedestrian detection, CVPR 2017, D. Xu et al.[PDF][Code]

    Pixel-level Fusion for Detection

    1. PCDFusion: Proposal-Context-Detail Bayesian Rendering for Infrared-Visible Image Fusion, Neurips 2026, Rui Liu et al., [PDF]
    2. RoES: Rotational Equivariant Selective-frequency Fusion for Multimodal Images, ACMMM 2026, Jiabao Wang, et al., [PDF][Code]
    3. P2Fusion: Prompt-based Progressive Infrared-Visible Image Fusion Via Dual-Prior Distillation, ECCV 2026, Yi Shi et al., [PDF][Code]
    4. RegionFuse: Region-Adaptive Pixel Distribution Learning for Infrared and Visible Image Fusion, CVPR 2026, Jianghan Xia et al., [PDF][Code]
    5. Fusion in Your Way: Aligning Image Fusion with Heterogeneous Demands via Direct Preference Optimization, CVPR 2026, Zengyi Yang et al., [PDF][Code]
    6. Customized Fusion: A Closed-Loop Dynamic Network for Adaptive Multi-Task-Aware Infrared-Visible Image Fusion, CVPR 2026, Yiming Sun et al., [PDF][Code]
    7. CtrlFuse: Mask-Prompt Guided Controllable Infrared and Visible Image Fusion, AAAI 2026, Yiming Sun et al., [PDF][Code]
    8. DDFD: Diffusion-Based Denoising Fusion for Object Detection in Infrared-Visible Images, ACM MM 2025, Min Dang et al., [PDF]
    9. LUT-Fuse: Towards Extremely Fast Infrared and Visible Image Fusion via Distillation to Learnable Look-Up Tables, ICCV 2025, Haodong Zhu et al., [PDF][Code]
    10. DCEvo: Discriminative Cross-Dimensional Evolutionary Learning for Infrared and Visible Image Fusion, CVPR 2025, Jinyuan Liu et al. [PDF][Code]
    11. Task-driven Image Fusion with Learnable Fusion Loss, CVPR 2025, Haowen Bai et al., [PDF][Code]
    12. DANet: A Dual-Branch Framework With Diffusion-Integrated Autoencoder for Infrared–Visible Image Fusion, TIM 2025, Chengyi Pan et al. [PDF][Code]
    13. RT-X Net: RGB-Thermal cross attention network for Low-Light Image Enhancement, ICIP 2025, Raman Jha et al., [PDF][Code]
    14. SFDFusion: An Efficient Spatial-Frequency Domain Fusion Network for Infrared and Visible Image Fusion, ECAI 2024, KunHu et al. [PDF][Code]
    15. E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion Detection, Neurips 2024, Jiaqing Zhang et al. [PDF][Code]
    16. Multi-modal Gated Mixture of Local-to-Global Experts for Dynamic Image Fusion, ICCV 2023, Yiming Sun et al.[PDF][Code]
    17. MetaFusion : Infrared and Visible Image Fusion via Meta-Feature Embedding from Object Detection, CVPR 2023, Wenda Zhao et al. [PDF][Code]
    18. Locality guided cross-modal feature aggregation and pixel-level fusion for multispectral pedestrian detection, Information Fusion 2022, Yanpeng Cao et al. [PDF]
    19. Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection, CVPR 2022, Jinyuan Liu et al.[PDF][Code]
    20. DetFusion: A Detection-driven Infrared and Visible Image Fusion Network, ACM Multimedia 2022, Yiming Sun et al. [PDF][Code]

    Illumination Aware

    1. Efficient Multispectral Object Detection with attentive feature aggregation leveraging zero-shot implicit illumination guidance, Information Fusion 2025, Zhongxia Xiong et al., [PDF]
    2. EI2Det: Edge-Guided Illumination-Aware Interactive Learning for Visible-Infrared Object Detection, TCSVT 2025, Ke Hu et al., [PDF] [Code]
    3. RGB-X Object Detection via Scene-Specific Fusion Modules, WACV 2024, Sri Aditya Deevi et al. [PDF] [Code]
    4. Illumination-Guided RGBT Object Detection With Inter- and Intra-Modality Fusion, IEEE Transactions on Instrumentation and Measurement 2023, Yan Zhang et al. [PDF][Code]
    5. IGT: Illumination-guided RGB-T object detection with transformers, Knowledge-Based Systems 2023, Keyu Chen et al. [PDF]
    6. Task-conditioned Domain Adaptation for Pedestrian Detection in Thermal Imagery, ECCV 2020, My Kieu et al. [PDF][Code]
    7. Improving Multispectral Pedestrian Detection by Addressing Modality Imbalance Problems, ECCV 2020, Kailai Zhou et al. [PDF][Code]
    8. Fusion of Multispectral Data Through Illumination-aware Deep Neural Networks for Pedestrian Detection, Information Fusion 2019, Dayan Guan et al.[PDF][Code]
    9. Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detection, Pattern Recognition 2018, Chengyang Li et al.[PDF][Code]

    Feature Alignment

    1. Contextually-Guided State Space Fusion for Misaligned Multi-Spectral Object Detection, ACMMM 2025, Guyue Jin et al., [PDF]
    2. CF-Deformable DETR: An End-to-End Alignment-Free Model for Weakly Aligned Visible-Infrared Object Detection, IJCAI 2024, Haolong Fu et al. [PDF][Code]
    3. C2Former: Calibrated and Complementary Transformer for RGB-Infrared Object Detection, TGRS 2024, Maoxun Yuan et al. [PDF][Code]
    4. Cross-Modality Proposal-guided Feature Mining for Unregistered RGB-Thermal Pedestrian Detection, TMM 2024, Chao Tian et al. [PDF]
    5. Multi-Modal Feature Pyramid Transformer for RGB-Infrared Object Detection, TITS 2023, Yaohui Zhu et al., [PDF]
    6. Attentive Alignment Network for Multispectral Pedestrian Detection, ACM MM 2023, Nuo Chen et al. [PDF]
    7. Towards Versatile Pedestrian Detector with Multisensory-Matching and Multispectral Recalling Memory, AAAI2022, Jung Uk Kim et al. [PDF]
    8. Mlpd: Multi-label pedestrian detector in multispectral domain, RAL 2021, Jiwon Kim et al. [PDF][Code]
    9. Weakly Aligned Feature Fusion for Multimodal Object Detection, TNNLS 2021, Lu Zhang et al. [PDF]
    10. Improving Multispectral Pedestrian Detection by Addressing Modality Imbalance Problems, ECCV 2020, Kailai Zhou et al. [PDF][Code]
    11. Weakly Aligned Cross-Modal Learning for Multispectral Pedestrian Detection, ICCV 2019, Lu Zhang et al.[PDF][Code]
    12. Multispectral Pedestrian Detection via Simultaneous Detection and Segmentation, BMVC 2018, Chengyang Li et al.[PDF][Code]

    Modality Translation and Knowledge Distillation

    1. InfraNet: Quality-Aware RGB Guidance for Infrared Object Detection, ECCV 2026, Zichao Feng et al., [PDF]
    2. Missing No More: Dictionary-Guided Cross-Modal Image Fusion under Missing Infrared, CVPR 2026, Yafei Zhang et al., [PDF][Code]
    3. SAM-Guided Semantic Knowledge Fusion for Visible-Infrared Object Detection, ACM MM 2025, Ting Li et al., [PDF][Code]
    4. Multimodal Decomposed Distillation with Instance Alignment and Uncertainty Compensation for Thermal Object Detection, ACM MM 2025, Yanfeng Liu et al. [PDF][Code]
    5. Rethinking Multi-modal Object Detection from the Perspective of Mono-Modality Feature Learning, ICCV 2025, Tianyi Zhao et al. [PDF][Code]
    6. Pseudo Visible Feature Fine-Grained Fusion for Thermal Object Detection, CVPR 2025, Ting Li et al. [PDF][Code]
    7. Modality Translation for Object Detection Adaptation Without Forgetting Prior Knowledge, ECCV 2024, Heitor R. Medeiros et al.,[PDF][Code]
    8. TIRDet: Mono-Modality Thermal InfraRed Object Detection Based on Prior Thermal-To-Visible Translation, ACM MM 2023, Zeyu Wang et al. [PDF][Code]
    9. Towards Versatile Pedestrian Detector with Multisensory-Matching and Multispectral Recalling Memory, AAAI 2022, Kim et al. [PDF]
    10. Robust Thermal Infrared Pedestrian Detection By Associating Visible Pedestrian Knowledge, ICASSP 2022, Sungjune Park et al. [PDF]
    11. Low-cost Multispectral Scene Analysis with Modality Distillation, Zhang Heng et al. [PDF]
    12. Task-conditioned Domain Adaptation for Pedestrian Detection in Thermal Imagery, ECCV 2020, My Kieu et al. [PDF][Code]
    13. Deep Cross-modal Representation Learning and Distillation for Illumination-invariant Pedestrian Detection, TCSCT 2021, T. Liu et al. [PDF]

    Fusion Architecture

    1. DETR is Secretly a Multispectral Detector: Zero-Parameter Adaptation via Semantic Alignment, ECCV 2026, Xiangyang Li et al., [PDF][Code]
    2. Efficient RGB-T Object Detection Via Sparse Cross-Modality Fusion, ECCV 2026, Chao Tian et al., [PDF]
    3. Bridging Multimodal Fusion and Expert Routing via Spectral Reliability Descriptors for Robust Object Detection, ACMMM 2026, Yefeng Wu, [PDF]
    4. Multispectral State-Space Feature Fusion: Bridging Shared and Cross-Parametric Interactions for Object Detection, Jifeng Shen et al. Information Fusion 2026, [PDF][Code]
    5. IRDFusion: Iterative relation-map difference guided feature fusion for multispectral object detection, Jifeng Shen et al. Pattern Recognition 2026 [PDF][Code]
    6. Removal Then Selection: A Coarse-to-Fine Fusion Perspective for RGB-Infrared Object Detection, TITS 2025, Tianyi Zhao et al. [PDF][Code)][知乎]
    7. WaveMamba: Wavelet-Driven Mamba Fusion for RGB-Infrared Object Detection, ICCV 2025, Haodong Zhu et al., [PDF][Code]
    8. Rethinking Early-Fusion Strategies for Improved Multispectral Object Detection, TIV 2025, Xue Zhang et al., [PDF][Code]
    9. Specificity-Guided Cross-Modal Feature Reconstruction for RGB-Infrared Object Detection, TITS 2024, Xiaoyu Sun et al., [PDF][Code]
    10. DAMSDet: Dynamic Adaptive Multispectral Detection Transformer with Competitive Query Selection and Adaptive Feature Fusion, ECCV 2024, Junjie Guo et al., [PDF][Code]
    11. TFDet: Target-Aware Fusion for RGB-T Pedestrian Detection, TNNLS 2024, Xue Zhang et al., [PDF][Code]
    12. Frequency Mining and Complementary Fusion Network for RGB-Infrared Object Detection, GRSL 2024, Yangfeixiao Liu et al., [PDF]
    13. M2FNet: Mask-guided Multi-level Fusion for RGB-T Pedestrian Detection, TMM 2024, Xiangyang Li et al., [PDF]
    14. ICAFusion: Iterative cross-attention guided feature fusion for multispectral object detection, Pattern Recognition 2024, Shen Jifeng et al. [PDF][Code]
    15. Improving RGB-infrared object detection with cascade alignment-guided transformer, Information Fusion 2024, Maoxun Yuan et al. [PDF]
    16. Multispectral Object Detection via Cross-Modal Conflict-Aware Learning, ACM MM 2023, Xiao He et al. [PDF][Code]
    17. Stabilizing Multispectral Pedestrian Detection with Evidential Hybrid Fusion, TCSVT 2023, Li Qing et al. [PDF]
    18. Multimodal Object Detection by Channel Switching and Spatial Attention, CVPRW 2023, Yue Cao et al. [PDF]
    19. Multi-Modal Feature Pyramid Transformer for RGB-Infrared Object Detection, TITS 2023, Yaohui Zhu et al. [PDF]
    20. Multiscale Cross-modal Homogeneity Enhancement and Confidence-aware Fusion for Multispectral Pedestrian Detection, TMM 2023, Ruimin Li et al. [PDF][Code]
    21. HAFNet: Hierarchical Attentive Fusion Network for Multispectral Pedestrian Detection, Remote Sensing 2023, Peiran Peng et al. [PDF]
    22. Multimodal Object Detection via Probabilistic Ensembling, ECCV2022, Yi-Ting Chen et al. [PDF][Code]
    23. Learning a Dynamic Cross-Modal Network for Multispectral Pedestrian Detection, ACM Multimedia 2022, Jin Xie et al. [PDF]
    24. Confidence-aware Fusion using Dempster-Shafer Theory for Multispectral Pedestrian Detection, TMM 2022, Qing Li et al. [PDF]
    25. Attention-Guided Multi-modal and Multi-scale Fusion for Multispectral Pedestrian Detection, PRCV 2022, Wei Bao et al. [PDF]
    26. Improving RGB-Infrared Pedestrian Detection by Reducing Cross-Modality Redundancy, ICIP2022, Qingwang Wang et al. [PDF]
    27. Spatio-contextual deep network-based multimodal pedestrian detection for autonomous driving, IEEE Transactions on Intelligent Transportation Systems, Kinjal Dasgupta et al. [PDF]
    28. Adopting the YOLOv4 Architecture for Low-LatencyMultispectral Pedestrian Detection in Autonomous Driving, Sensors 2022, Kamil Roszyk et al. [PDF]
    29. Deep Active Learning from Multispectral Data Through Cross-Modality Prediction Inconsistency, ICIP2021, Heng Zhang et al.[PDF]
    30. Attention Fusion for One-Stage Multispectral Pedestrian Detection, Sensors 2021, Zhiwei Cao et al. [PDF]
    31. Uncertainty-Guided Cross-Modal Learning for Robust Multispectral Pedestrian Detection, IEEE Transactions on Circuits and Systems for Video Technology 2021, Jung Uk Kim et al. [PDF]
    32. Deep Cross-modal Representation Learning and Distillation for Illumination-invariant Pedestrian Detection, IEEE Transactions on Circuits and Systems for Video Technology 2021, T. Liu et al. [PDF]
    33. Guided Attentive Feature Fusion for Multispectral Pedestrian Detection, WACV 2021, Heng Zhang et al. [PDF]
    34. Anchor-free Small-scale Multispectral Pedestrian Detection, BMVC 2020, Alexander Wolpert et al. [PDF][Code]
    35. Multispectral Fusion for Object Detection with Cyclic Fuse-and-Refine Blocks, ICIP 2020, Heng Zhang et al. [PDF]
    36. Improving Multispectral Pedestrian Detection by Addressing Modality Imbalance Problems, ECCV 2020, Kailai Zhou et al. [PDF][Code]
    37. Anchor-free Small-scale Multispectral Pedestrian Detection, BMVC 2020, Alexander Wolpert et al. [PDF][Code]
    38. Weakly Aligned Cross-Modal Learning for Multispectral Pedestrian Detection, ICCV 2019, Lu Zhang et al. [PDF][Code]
    39. Box-level Segmentation Supervised Deep Neural Networks for Accurate and Real-time Multispectral Pesdestrian Detecion, ISPRS Journal of Photogrammetry and Remote Sensing 2019, Yanpeng Cao et al.[PDF][Code]
    40. Cross-modality interactive attention network for multispectral pedestrian detection, Information Fusion 2019, Lu Zhang et al.[PDF][Code]
    41. Pedestrian detection with unsupervised multispectral feature learning using deep neural networks, Information Fusion 2019, Cao, Yanpeng et al.[PDF]
    42. Multispectral Pedestrian Detection via Simultaneous Detection and Segmentation, BMVC 2018, Chengyang Li et al.[PDF][Code][Project Link]
    43. Unified Multi-spectral Pedestrian Detection Based on Probabilistic Fusion Networks, Pattern Recognition 2018, Kihong Park et al.[PDF]
    44. Multispectral Deep Neural Networks for Pedestrian Detection, BMVC 2016, Jingjing Liu et al.[PDF][Code]
    45. Multispectral Pedestrian Detection Benchmark Dataset and Baseline, 2015, Soonmin Hwang et al.[PDF][Code]

    Adversarial Attack and Defense

    1. MEC-Patch: Visible-Infrared Cross-Modal Adversarial Attack Driven by Intrinsic Material Emissivity Laws, Zhixiang Huang et al., ACM MM 2026, [PDF][Code]
    2. Physical Adversarial Clothing Evades Visible-Thermal Detectors Via Non-Overlapping RGB-T Pattern, CVPR 2026, Xiaopei Zhu et al., [PDF][Code]
    3. CDUPatch: Color-Driven Universal Adversarial Patch Attack for Dual-Modal Visible-Infrared Detectors, Jiahuan Long et al., ACM MM 2025, [PDF]
    4. PAIF: Perception-Aware Infrared-Visible Image Fusion for Attack-Tolerant Semantic Segmentation, Zhu Liu et al., ACM MM 2023, [PDF][Code]

    RGB-T Aerial Object Detection

    Datasets

    Dataset Years Modality Images Classes Alignment
    DroneVehicle 2021 RGB, LWIR 56K 5 Partially
    VEDAI 2014 RGB, NIR 1K 9 Strictly
    NII-CU 2022 RGB, LWIR 5K 1 Strictly
    DVTOD 2024 RGB, LWIR 2K 3 Misaligned
    VTSaR 2024 RGB, LWIR 40K 1 Strictly
    RGBT-Tiny 2025 RGB, LWIR 93K 7 Partially
    ATR-UMOD 2025 RGB, LWIR 13K 11 Partially
    MODA 2026 RGB, NIR 13K 8 Strictly
    Tri-Modal Dataset 2026 RGB, LWIR, Event 10K 1 Partially

    Papers

    1. DyFCLT: Dynamic Frequency-Decoupled Cross-Modal Learning Transformer for Multimodal Tiny Object Detection, CVPR 2026, Chaolang Li et al., [PDF]
    2. Unifying Heterogeneous Multi-Modal Remote Sensing Detection Via Language-Pivoted Pretraining, ICML 2026,Yuxuan Li et al., [PDF][Code]
    3. Bridging Multimodal Fusion and Expert Routing via Spectral Reliability Descriptors for Robust Object Detection, ACMMM 2026, Yefeng Wu, [PDF]
    4. IRAA: Information Redistribution Adversarial Attacks for Multimodal Object Detection, ACMMM 2026, Sixu Liu et al., [PDF]
    5. AIR-Det: Asymmetric Multimodal Object Detection via Main-Conditioned Residual Learning, ACMMM 2026, Ziang Gan et al., [PDF]
    6. Beyond RGB: Mining Simulated IR Priors for RGB-only UAV Detection in Unlabeled Real Scenarios, ACMMM 2026, Qiulu Li et al., [PDF]
    7. Tri-Modal Fusion Transformers for UAV-based Object Detection, CVPR 2026, Craig Iaboni et al., [PDF][Code]
    8. MODA: The First Challenging Benchmark for Multispectral Object Detection in Aerial Images, AAAI 2026, Shuaihao Han et al., [PDF][Code]
    9. SM3Det: A Unified Model for Multi-Modal Remote Sensing Object Detection, AAAI 2026, Yuxuan Li et al., [PDF][Code]
    10. IGIANet: Illumination Guided Implicit Alignment Network for Infrared–Visible UAVDetection, AAAI 2026, Xiangqi Chen et al., [PDF]
    11. Contextually-Guided State Space Fusion for Misaligned Multi-Spectral Object Detection, ACMMM 2025, Guyue Jin et al., [PDF]
    12. Fusion Meets Diverse Conditions: A High-diversity Benchmark and Baseline for UAV-based Multimodal Object Detection with Condition Cues, ICCV 2025, Chen Chen et al., [PDF]
    13. Rethinking Multi-modal Object Detection from the Perspective of Mono-Modality Feature Learning, ICCV 2025, Tianyi Zhao et al., [PDF][Code]
    14. Detection-Friendly Nonuniformity Correction: A Union Framework for Infrared UAV Target Detection, CVPR 2025, Houzhang Fang et al. [PDF][Code]
    15. SFFR: Spatial-Frequency Feature Reconstruction for Multispectral Aerial Object Detection, TGRS 2025, Xin Zuo et al. [PDF][Code]
    16. Reflectance-Guided Progressive Feature Alignment Network for All-Day UAV Object Detection, TGRS 2025, Zhicheng Zhao et al., [PDF][Code]
    17. Visible-Infrared Image Alignment For Unmanned Aerial Vehicles: Benchmark and New Baseline, TGRS 2025, Zhinan Gao et al., [PDF][Code]
    18. LAST-Net: Local Adaptivity Spatial Transformer Network for Multiobject Detection in UAV Remote Sensing Thermal Infrared Imagery, TGRS 2025, Min Li et al., [PDF]
    19. Visible-Thermal Tiny Object Detection: A Benchmark Dataset and Baselines, TPAMI 2025, Xinyi Ying et al., [PDF][Code]
    20. Aerial image object detection based on RGB-Infrared multi-branch progressive fusion, TGRS 2025, Kewei Liu et al., [PDF]
    21. Dual Dynamic Cross-modal Interaction Network for Multimodal Remote Sensing Object Detection, TGRS 2025, Wei Bao et al., [PDF][Code]
    22. Unified multimodal fusion transformer for few shot object detection for remote sensing images, Information Fusion 2024, Abdullah Azeem et al., [PDF]
    23. SM3Det: A Unified Model for Multi-Modal Remote Sensing Object Detection, Yuxuan Li et al., Arxiv 2025, [PDF][Code]
    24. CCLDet: A Cross-Modality and Cross-Domain Low-Light Detector, Xiping Shang et al., TITS 2025, [PDF]
    25. Dual-Dynamic Cross-Modal Interaction Network for Multimodal Remote Sensing Object Detection, TGRS 2025, Wei Bao et al., [PDF][Code]
    26. DAMSDet: Dynamic Adaptive Multispectral Detection Transformer with Competitive Query Selection and Adaptive Feature Fusion, ECCV 2024, Junjie Guo et al., [PDF][Code]
    27. Cross Teaching-Enhanced Multi-spectral Remote Sensing Object Detection with Transformer, TGRS 2024, Jiahe Zhu et al., [PDF]
    28. Cross-Modal Oriented Object Detection of UAV Aerial Images Based on Image Feature, TGRS 2024, Huiying Wang et al., [PDF]
    29. CMDistill: Cross-modal Distillation Framework for UAV Image Object Detection, JSTAR 2024, Xiaozhong Tong et al., [PDF]
    30. Multimodal Feature-Guided Pretraining for RGB-T Perception, JSTAR 2024, Junlin Ouyang et al., [PDF]
    31. Mask-Guided Mamba Fusion for Drone-based Visible-Infrared Vehicle Detection, TGRS 2024, Simiao Wang et al., [PDF]
    32. Low-rank Multimodal Remote Sensing Object Detection with Frequency Filtering Experts, TGRS 2024, Xu Sun et al., [PDF][Code]
    33. Weakly Misalignment-free Adaptive Feature Alignment for UAVs-based Multimodal Object Detection, CVPR 2024, Chen Chen et al., [PDF]
    34. Misaligned Visible-Thermal Object Detection: A Drone-based Benchmark and Baseline, TIV 2024, Kechen Song, [PDF][Code]
    35. C2Former: Calibrated and Complementary Transformer for RGB-Infrared Object Detection, TGRS 2024, Maoxun Yuan et al. [PDF][Code]
    36. ICAFusion: Iterative cross-attention guided feature fusion for multispectral object detection, Pattern Recognition 2024, Shen Jifeng et al. [PDF][Code]
    37. Improving RGB-infrared object detection with cascade alignment-guided transformer, Information Fusion 2024, Maoxun Yuan et al. [PDF]
    38. Multispectral Object Detection via Cross-Modal Conflict-Aware Learning, ACM MM 2023, Xiao He et al. [PDF][Code]
    39. LRAF-Net: Long-Range Attention Fusion Network for Visible–Infrared Object Detection, TNNLS 2023, Haolong Fu et al. [PDF]
    40. Modality Balancing Mechanism for RGB-Infrared Object Detection in Aerial Image, PRCV 2023, Weibo Cai er al., [PDF]
    41. RGB-Infrared Multi-Modal Remote Sensing Object Detection Using CNN and Transformer Based Feature Fusion, IGARSS 2023, Tao Tian et al., [PDF]
    42. GF-Detection: Fusion with GAN of Infrared and Visible Images for Vehicle Detection at Nighttime, Remote Sensing 2022, Peng Gao et al. [PDF]
    43. Cross-modality attentive feature fusion for object detection in multispectral remote sensing imagery, Pattern Recognition, Qingyun Fang et al. [PDF]
    44. Translation, Scale and Rotation: Cross-Modal Alignment Meets RGB-Infrared Vehicle Detection, ECCV 2022, Maoxun Yuan et al. [PDF]
    45. Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning, TCSVT 2022, Yiming Sun [PDF][Code]
    46. Improving RGB-Infrared Object Detection by Reducing Cross-Modality Redundancy, Remote Sensing 2022, Qingwang Wang et al. [PDF]

    RGB-T Semantic Segmentation

    Datasets

    Dataset Years Modality Images Classes
    MFNet 2017 RGB, LWIR 1.5K 8
    PST900 2020 RGB, LWIR 900 5
    SemanticRT 2023 RGB, LWIR 11K 13
    FMB 2023 RGB, LWIR 1.5K 14
    IDD-AW (Adverse Weather) 2023 RGB, NIR 5K 18
    Caltech Aerial RGBT 2024 RGB, LWIR 4K 10

    Papers

    1. Towards Unsupervised Multi-modal Semantic Segmentation, ECCV 2026, Haitian Zhang et al., [PDF]
    2. UniRGB-IR: A Unified Framework for Visible-Infrared Downstream Tasks via Adapter Tuning, ACM MM 2025, Maoxun Yuan et al., [PDF][Code]
    3. StitchFusion: Weaving Any Visual Modalities to Enhance Multimodal Semantic Segmentation, ACMMM 2025, Bingyu Li et al., [PDF][Code]
    4. AMDANet: Attention-Driven Multi-Perspective Discrepancy Alignment for RGB-Infrared Image Fusion and Segmentation, ICCV 2025, Haifeng Zhong et al., [PDF][Code]
    5. Every SAMDrop Counts: Embracing Semantic Priors for Multi-Modality Image Fusion and Beyond, CVPR 2025, Guanyao Wu et al., [PDF][Code]
    6. Task-driven Image Fusion with Learnable Fusion Loss, CVPR 2025, Haowen Bai et al., [PDF][Code]
    7. Knowledge Distillation SegFormer-Based Network for RGB-T Semantic Segmentation, TCYB 2024, Wujie Zhou et al,. [PDF][Code]
    8. Caltech Aerial RGB-Thermal Dataset in the Wild, ECCV 2024, Connor Lee et al,. [PDF][Code]
    9. Context-Aware Interaction Network for RGB-T Semantic Segmentation, TMM 2024, Ying Lv et al. [PDF][Code]
    10. Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation, Jinyuan Liu et al., [PDF][Code]
    11. CACFNet: Cross-Modal Attention Cascaded Fusion Network for RGB-T Urban Scene Parsing, TIV 2023, Wujie Zhou et al., [PDF]
    12. On Exploring Shape and Semantic Enhancements for RGB-X Semantic Segmentation, TIV 2023, Yuanjian Yang et al., [PDF][Code]
    13. Complementarity-aware cross-modal feature fusion network for RGB-T semantic segmentation, PR 2023, Wei Wu et al., [PDF]
    14. MMSMCNet: Modal Memory Sharing and Morphological Complementary Networks for RGB-T Urban Scene Semantic Segmentation, TCSVT 2023, Wujie Zhou et al. [PDF][Code]
    15. SGFNet: Semantic-Guided Fusion Network for RGB-Thermal Semantic Segmentation, TCSVT 2023, Yike Wang et al., [PDF][Code]
    16. DBCNet: Dynamic Bilateral Cross-Fusion Network for RGB-T Urban Scene Understanding in Intelligent Vehicles, TCYB 2023, Wujie Zhou et al., [PDF]
    17. Explicit Attention-Enhanced Fusion for RGB-Thermal Perception Tasks, RAL 2023, Mingjian Liang et al., [PDF][Code]
    18. Embedded Control Gate Fusion and Attention Residual Learning for RGB–Thermal Urban Scene Parsing, TITS 2023, Wujie Zhou et al., [PDF]
    19. UTFNet: Uncertainty-Guided Trustworthy Fusion Network for RGB-Thermal Semantic Segmentation, GRSL 2023, Qingwang Wang et al., [PDF][Code]
    20. Efficient Multimodal Semantic Segmentation via Dual-Prompt Learning, arxiv 2023, Shaohua Dong et al., [PDF][Code]
    21. A RGB-Thermal Image Segmentation Method Based on Parameter Sharing and Attention Fusion for Safe Autonomous Driving, TITS 2023, Guofa Li et al., [PDF]
    22. SFAF-MA: Spatial Feature Aggregation and Fusion With Modality Adaptation for RGB-Thermal Semantic Segmentation, TIM 2023, Xunjie He et al., [PDF][Code]
    23. Edge-aware guidance fusion network for RGB–thermal scene parsing, AAAI 2022, Wujie Zhou et al., [PDF][Code]
    24. CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers, TITS 2022, Jiaming Zhang et al., [PDF][Code]
    25. RGB-T Semantic Segmentation with Location, Activation, and Sharpening, TCSVT 2022, Gongyang Li et al., [PDF][Code]
    26. A Feature Divide-and-Conquer Network for RGB-T Semantic Segmentation, TCSVT 2022, Shenlu Zhao et al., [PDF]
    27. CCAFFMNet: Dual-spectral semantic segmentation network with channel-coordinate attention feature fusion module, Neurocomputing 2022, [PDF]
    28. CGFNet: cross-guided fusion network for RGB-thermal semantic segmentation, The Visual Computer 2022, Yanping Fu et al., [PDF]
    29. MTANet: Multitask-Aware Network with Hierarchical Multimodal Fusion for RGB-T Urban Scene Understanding, TIV 2022, Wujie Zhou et al., [PDF][Code]
    30. GCNet: Grid-Like Context-Aware Network for RGB-Thermal Semantic Segmentation, Neurocomputing 2022, Jinfu Liu et al., [PDF]
    31. ABMDRNet: Adaptive-weighted Bi-directional Modality Difference Reduction Network for RGB-T Semantic Segmentation, CVPR 2021, Qiang Zhang et al., [PDF]
    32. GMNet: Graded-Feature Multilabel-Learning Network for RGB-Thermal Urban Scene Semantic Segmentation, TIP 2021, Wujie Zhou et al., [PDF][Code]
    33. MFFENet: Multiscale Feature Fusion and Enhancement Network for RGBThermal Urban Road Scene Parsing, TMM 2021, Wujie Zhou et al., [PDF]
    34. FEANet: Feature-Enhanced Attention Network for RGB-Thermal Real-time Semantic Segmentation, IROS 2021, Fuqin Deng et al., [PDF][Code]
    35. HeatNet: Bridging the Day-Night Domain Gap in Semantic Segmentation with Thermal Images, IROS 2021, Johan Vertens et al., [PDF]
    36. Robust semantic segmentation based on RGB-thermal in variable lighting scenes, Measurement 2021, Zhifeng Guo et al., [PDF]
    37. FuseSeg: Semantic segmentation of urban scenes based on RGB and thermal data fusion, TASE 2020, Yuxiang Sun et al., [PDF]
    38. PST900: RGB-Thermal Calibration, Dataset and Segmentation Network, ICRA 2020, Shreyas S. Shivakumar et al., [PDF][Code]
    39. RTFNet: RGB-Thermal Fusion Network for Semantic Segmentation of Urban Scenes, RAL 2019, Yuxiang Sun et al., [PDF][Code]
    40. MFNet: Towards Real-Time Semantic Segmentation for Autonomous Vehicles with Multi-Spectral Scenes, IROS 2019, Qishen Ha et al., [PDF][Code]

    RGB-T Salient Object Detection

    Datasets

    VT821 Dataset [PDF][link], VT1000 Dataset [PDF][link], VT5000 Dataset [PDF][link[9yqv]], VI-RGBT1500 Dataset[PDF][link], UVT2000 Dataset[PDF][link]

    Papers

    1. Liquid Fusion of Heterogeneous Representations Towards General Salient Object Detection, ECCV 2026, Ke Chen et al., [PDF][Code]
    2. RA-SOD: Reliability-Aware RGB-T Salient Object Detection Under Modality Degradation, ECCV 2026, Hongbo Gao et al., [PDF][Code]
    3. Uncertainty-Aware Modality Fusion for Unaligned RGB-T Salient Object Detection, CVPR 2026, Mianzhao Wang et al., [PDF]
    4. UniRGB-IR: A Unified Framework for Visible-Infrared Downstream Tasks via Adapter Tuning, ACM MM 2025, Maoxun Yuan et al., [PDF][Code]
    5. Divide-and-Conquer: Confluent Triple-Flow Network for RGB-T Salient Object Detection, TPAMI 2024, Hao Tang et al., [PDF][Code]
    6. Alignment-Free RGBT Salient Object Detection: Semantics-guided Asymmetric Correlation Network and A Unified Benchmark, TMM 2024, Kunpeng Wang et al., [PDF][Code]
    7. VST++: Efficient and Stronger Visual Saliency Transformer, TPAMI 2024, Nian Liu et al., [PDF][Code]
    8. UniTR: A Unified TRansformer-based Framework for Co-object and Multi-modal Saliency Detection, TMM 2024, Ruohao Guo et al., [PDF]
    9. Learning Adaptive Fusion Bank for Multi-modal Salient Object Detection, TCSVT 2024, Kunpeng Wang et al., [PDF]
    10. TMNet: Triple-modal interaction encoder and multi-scale fusion decoder network for V-D-T salient object detection, PR 2024, Bin Wan et al., [PDF]
    11. Weighted Guided Optional Fusion Network for RGB-T Salient Object Detection, TOMM 2024, Jie Wang et al., [PDF][Code]
    12. Position-Aware Relation Learning for RGB-Thermal Salient Object Detection, TIP 2023, Heng Zhou et al., [PDF]
    13. WaveNet: Wavelet Network With Knowledge Distillation for RGB-T Salient Object Detection, TIP 2023, Wujie Zhou et al., [PDF][Code]
    14. LSNet: Lightweight Spatial Boosting Network for Detecting Salient Objects in RGB-Thermal Images, TIP 2023, Wujie Zhou et al., [PDF][Code]
    15. CAVER: Cross-Modal View-Mixed Transformer for Bi-Modal Salient Object Detection, TIP 2023, Youwei Pang et al., [PDF][Code]
    16. Glass Segmentation With RGB-Thermal Image Pairs, TIP 2023, Dong Huo et al., [PDF][Code]
    17. MFFNet: Multi-modal Feature Fusion Network for V-D-T Salient Object Detection, TMM 2023, Bin Wan et al., [PDF]
    18. LFTransNet: Light Field Salient Object Detection via a Learnable Weight Descriptor, TCSVT 2023, Zhengyi Liu et al., [PDF][Code]
    19. Multiple Graph Affinity Interactive Network and a Variable Illumination Dataset for RGBT Image Salient Object Detection, TCSVT 2023, Kechen Song et al., [PDF][Code]
    20. Cross-Modality Double Bidirectional Interaction and Fusion Network for RGB-T Salient Object Detection, TCSVT 2023, Zhengxuan Xie et al., [PDF]
    21. DBCNet: Dynamic Bilateral Cross-Fusion Network for RGB-T Urban Scene Understanding in Intelligent Vehicles, TCYB 2023, [PDF]
    22. Frequency-aware feature aggregation network with dual-task consistency for RGB-T salient object detection, PR 2023, Heng Zhou et al. [PDF]
    23. Cross-modal co-feedback cellular automata for RGB-T saliency detection, PR 2023, Yu Pang et al., [PDF]
    24. An interactively reinforced paradigm for joint infrared-visible image fusion and saliency object detection, Information Fusion 2023, Di Wang et al., [PDF][Code]
    25. Thermal images-aware guided early fusion network for cross-illumination RGB-T salient object detection, EAAI 2023, Han Wang et al., [PDF][Code]
    26. Explicit Attention-Enhanced Fusion for RGB-Thermal Perception Tasks, RAL 2023, Mingjian Liang et al., [PDF][Code]
    27. MENet: Lightweight multimodality enhancement network for detecting salient objects in RGB-thermal images, Neurocomputing 2023, Junyi Wu et al., [PDF]
    28. Feature aggregation with transformer for RGB-T salient object detection, Neurocomputing 2023, Ping Zhang et al., [PDF][Code]
    29. Texture-Guided Saliency Distilling for Unsupervised Salient Object Detection, CVPR2023, Huajun Zhou et al., [PDF][Code]
    30. Saliency Prototype for RGB-D and RGB-T Salient Object Detection, ACM MM 2023, Zihao Zhang et al., [PDF][Code]
    31. ADNet: An Asymmetric Dual-Stream Network for RGB-T Salient Object Detection, ACM MM 2023, Yaqun Fang et al., [PDF]
    32. Scribble-Supervised RGB-T Salient Object Detection, ICME 2023, Zhengyi Liu et al., [PDF][Code]
    33. Feature Enhancement and Fusion for RGB-T Salient Object Detection, ICIP 2023, Fengming Sun et al., [PDF]
    34. Weakly Alignment-free RGBT Salient Object Detection with Deep Correlation Network, TIP 2022, Zhengzheng Tu et al., [PDF][Code]
    35. Cross-modal co-feedback cellular automata for RGB-T saliency detection, PR 2022, Yu Pang et al., [PDF]
    36. RGBT Salient Object Detection: A Large-Scale Dataset and Benchmark, TMM 2022, Zhengzheng Tu et al., [PDF]
    37. Does Thermal really always matter for RGB-T salient object detection, TMM 2022, Runmin Cong et al., [PDF][Code]
    38. TCNet: Co-Salient Object Detection via Parallel Interaction of Transformers and CNNs, TCSVT 2023, Yanliang Ge et al., [PDF][Code]
    39. Modality-Induced Transfer-Fusion Network for RGB-D and RGB-T Salient Object Detection, TCSVT 2022, Gang Chen et al., [PDF]
    40. Cross-Collaborative Fusion-Encoder Network for Robust RGB-Thermal Salient Object Detection, TCSVT 2022, Guibiao Liao et al., [PDF][Code]
    41. CGMDRNet: Cross-Guided Modality Difference Reduction Network for RGB-T Salient Object Detection, TCSVT 2022, Gang Chen et al., [PDF]
    42. RGB-T Semantic Segmentation With Location, Activation, and Sharpening, TCSVT 2022, Gongyang Li et al., [PDF][Code]
    43. HRTransNet: HRFormer-Driven Two-Modality Salient Object Detection, TCSVT 2022, Bin Tang et al., [PDF][Code]
    44. Asymmetric cross-modal activation network for RGB-T salient object detection, KBS 2022, Chang Xu et al., [PDF][Code]
    45. Three-stream interaction decoder network for RGB-thermal salient object detection, KBS 2022, Fushuo Huo et al., [PDF][Code]
    46. Real-time One-stream Semantic-guided Refinement Network for RGB-Thermal Salient Object Detection, TIM 2022, Fushuo Huo et al., [PDF][Code]
    47. Multi-modal Interactive Attention and Dual Progressive Decoding Network for RGB-D/T Salient Object Detection, Neurocomputing 2022, Yanhua Liang et al., [PDF][Code]
    48. PSNet: Parallel symmetric network for RGB-T salient object detection, Neurocomputing 2022, Hongbo Bi et al., [PDF]
    49. Mirror Complementary Transformer Network for RGB-thermal Salient Object Detection, arxiv 2022, [PDF][Code]
    50. Bimodal Information Fusion Network for Salient Object Detection based on Transformer, PRML 2022, Zhuo Wang et al., [PDF]
    51. Multi-Interactive Dual-Decoder for RGB-Thermal Salient Object Detection, TIP 2021, Zhengzheng Tu et al., [PDF][Code]
    52. ECFFNet: Effective and Consistent Feature Fusion Network for RGB-T Salient Object Detection, TCSVT 2021, Wujie Zhou et al., [PDF]
    53. SwinNet: Swin Transformer drives edge-aware RGB-D and RGB-T salient object detection, TCSVT 2021, [PDF][Code]
    54. Unified Information Fusion Network for Multi-Modal RGB-D and RGB-T Salient Object Detection, TCSVT 2021, Wei Gao et al., [PDF]
    55. Multi-graph Fusion and Learning for RGBT Image Saliency Detection, TCSVT 2021, Liming Huang et al., [PDF]
    56. CGFNet: Cross-Guided Fusion Network for RGB-T Salient Object Detection, TCSVT 2021, Jie Wang et al., [PDF][Code]
    57. Efficient Context-Guided Stacked Refinement Network for RGB-T Salient Object Detection, TCSVT 2021, Fushuo Huo et al., [PDF][Code]
    58. RGB-T Salient Object Detection via Fusing Multi-Level CNN Features, TIP 2020, Qiang Zhang et al., [PDF][Code]
    59. Revisiting Feature Fusion for RGB-T Salient Object Detection, TCSCT 2020, Qiang Zhang et al., [PDF][Code]
    60. Deep Domain Adaptation Based Multi-Spectral Salient Object Detection, TMM 2020, Shaoyue Song et al., [PDF]
    61. Abiotic Stress Prediction from RGB-T Images of Banana Plantlets, ECCV 2020, Sagi Levanon et al., [PDF]
    62. Multi-Spectral Salient Object Detection by Adversarial Domain Adaptation, AAAI 2020, Shaoyue Song et al.[PDF]
    63. Deep Domain Adaptation Based Multi-spectral Salient Object Detection, TMM 2020, Shaoyue Song et al., [PDF]
    64. RGB-T Image Saliency Detection via Collaborative Graph Learning, TMM 2019, Zhengzheng Tu et al., [PDF][Code]
    65. RGBT Salient Object Detection: Benchmark and A Novel Cooperative Ranking Approach, TCSVT 2019, Jin Tang et al., [PDF][Code]
    66. M3S-NIR: Multi-Modal Multi-Scale Noise-Insensitive Ranking for RGB-T Saliency Detection, MIPR 2019, Zhengzheng Tu et al., [PDF][Code]
    67. RGB-T Saliency Detection Benchmark: Dataset, Baselines, Analysis and a Novel Approach, IGTA 2018, Guizhao Wang et al., [PDF][Code]
    68. Learning Multiscale Deep Features and SVM Regressors for Adaptive RGB-T Saliency Detection, ISCID 2017, Yunpeng Ma et al., [PDF]

    RGB-T Crowd Counting

    Datasets

    RGBT-CC[link], DroneRGBT [link]

    Papers

    1. Closing the Modality Gap without Pixel-wise Registration: Geometric-Semantic Tri-Optimization for Misaligned Infrared-Visible Image Segmentation, ACMMM 2026, Tingyu Shi et al., [PDF][Code]

    2. Free Lunch Enhancements for Multi-modal Crowd Counting, CVPR 2025, Haoliang Meng et al. [PDF][Code]

    3. CCANet: A Collaborative Cross-modal Attention Network for RGB-D Crowd Counting, TMM2023, Yanbo Liu et al. [PDF]

    4. MC3Net: Multimodality Cross-Guided Compensation Coordination Network for RGB-T Crowd Counting, TITS 2023, Wujie Zhou et al. [PDF]

    5. RGB-T Multi-Modal Crowd Counting Based on Transformer, BMVC 2022, Zhengyi Liu et al. [PDF]

    6. Spatio-channel Attention Blocks for Cross-modal Crowd Counting, ACCV2022, Youjia Zhang et al. [PDF]

    7. DEFNet: Dual-Branch Enhanced Feature Fusion Network for RGB-T Crowd Counting, TITS 2022, Zhou, Wujie et al. [PDF]

    8. MAFNet: A Multi-Attention Fusion Network for RGB-T Crowd Counting, arxiv2022, Pengyu Chen et al. [PDF]

    9. Multimodal Crowd Counting with Mutual Attention Transformers, ICME 2022, Wu, Zhengtao et al. [PDF]

    10. Conditional RGB-T Fusion for Effective Crowd Counting, ICIP 2022, Esha Pahwa et al. [PDF]

    11. Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting, CVPR2021, Lingbo Liu et al. [PDF][Code]

    12. RGB-T Crowd Counting from Drone: A Benchmark and MMCCN Network, ACCV2020, Tao Peng et al. [PDF][Code]


    RGB-T Fusion Tracking

    Datasets

    GTOT [PDF][link], RGBT234 Dataset [PDF][link], LasHeR Dataset [PDF][link], UniRTL Dataset [PDF][Code]

    Papers

    1. Progressive Multi-cue Alignment for Unaligned RGBT Tracking, CVPR 2026, Jiandong Jin et al., [PDF]
    2. Local-to-global Cross-modal Coordination for Self-supervised RGB-T Tracking, ECCV 2026, Yueying Zhang et al., [PDF][Code]
    3. RT-RMOT: A Dataset and Framework for RGB-Thermal Referring Multi-Object Tracking, ECCV 2026, Yanqiu Yu et al., [PDF]
    4. GAP-Track: Bridging The Resolution Gap for Cross-Resolution RGBT Tracking, ECCV 2026, Shiyu Zhang et al., [PDF][Code]
    5. OCTA-SOT: Online Cross-Modal Trajectory Adjustment for RGBT Anti-UAV Single Object Tracking under Spatio-Temporal Misalignment, ECCV 2026, Xiaokang Liu et al., [PDF][Code]
    6. SEATrack: Simple, Efficient, and Adaptive Multimodal Tracker, CVPR 2026, Junbin Su et al., [PDF][Code]
    7. Adaptive Depth Lightweight RGB-T Tracking with Holistic Token Routing, CVPR 2026, Tian Ding et al., [PDF]
    8. RAGTrack: Language-aware RGBT Tracking with Retrieval-Augmented Generation, CVPR 2026, Hao Li et al., [PDF]
    9. Unaligned UAV RGBT Tracking: A Largescale Benchmark and a Novel Approach, AAAI 2026, Yun Xiao et al., [PDF]
    10. UniRTL: A universal RGBT and low-light benchmark for object tracking, Pattern Recognition 2025, Lian Zhang et al. [PDF][Code]
    11. MTNet: Learning Modality-aware Representation with Transformer for RGBT Tracking, ICME 2023, Ruichao Hou et al. [PDF]
    12. Visual Prompt Multi-Modal Tracking, CVPR 2023, Jiawen Zhu et al. [PDF][Code]
    13. Efficient RGB-T Tracking via Cross-Modality Distillation, CVPR 2023, Zhang, Tianlu et al. [PDF]
    14. Bridging Search Region Interaction with Template for RGB-T Tracking, Hui, CVPR2023, Tianrui et al.[PDF][Code]
    15. Jointly Modeling Motion and Appearance Cues for Robust RGB-T Tracking, TIP2021, Zhang, Pengyu et al. [PDF] TIP 2022, Tu, Zhengzheng et al., [PDF]
    16. RGBT tracking via reliable feature configuration, SCIS 2022, Tu, Zhengzheng et al. [PDF]
    17. Attribute-Based Progressive Fusion Network for RGBT Tracking, AAAI 2022, Xiao Yun et al. [PDF][Code]
    18. Dense Feature Aggregation and Pruning for RGBT Tracking, ACM Multimedia 2022, Yabin Zhu et al. [PDF]
    19. Prompting for Multi-Modal Tracking, ACM Multimedia 2022, Jinyu Yang et al. [PDF]
    20. Learning Adaptive Attribute-Driven Representation for Real-Time RGB-T Tracking, IJCV 2021, Zhang, Pengyu et al. [PDF]
    21. Quality-Aware Feature Aggregation Network for Robust RGBT Tracking, TIV 2021, Zhu, Yabin, [PDF]
    22. Challenge-Aware RGBT Tracking, ECCV 2020, Li Chenglong et al. [PDF]
    23. Object fusion tracking based on visible and infrared images: A comprehensive review, Information Fusion 2020, Zhang, Xingchen et al., [PDF]
    24. RGB-T object tracking: Benchmark and baseline, Pattern Recognition 2019, Li, Chenglong et al., [PDF]
    25. Cross-Modal Pattern-Propagation for RGB-T Tracking, CVPR2020, Chaoqun Wang et al., [PDF]

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