多模态信息融合

Learning Modal-Invariant and Temporal-Memory for Video-based Visible-Infrared Person Re-Identification

Xinyu Lin, Jinxing Li, Zeyu Ma, Huafeng Li, Shuang Li, Kaixiong Xu, Guangming Lu, David Zhang

专题命中 红外-可见光融合 ：visible-infrared(title,abstract)；分类 cs.CV

Journal ref Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, pp. 20973-20982

SwinFuse: A Residual Swin Transformer Fusion Network for Infrared and Visible Images

Zhishe Wang, Yanlin Chen, Wenyu Shao, Hui Li, Lei Zhang

专题命中 红外-可见光融合 ：infrared and visible(title,abstract)；分类 cs.CV

Comments 12pages, 19figures

Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection

Jinyuan Liu, Xin Fan, Zhanbo Huang, Guanyao Wu, Risheng Liu, Wei Zhong, Zhongxuan Luo

专题命中 红外-可见光融合 ：infrared and visible(title,abstract)；分类 cs.CV

Comments Accepted by IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022. (Oral)

On Exploring Pose Estimation as an Auxiliary Learning Task for Visible-Infrared Person Re-identification

Yunqi Miao, Nianchang Huang, Xiao Ma, Qiang Zhang, Jungong Han

专题命中 红外-可见光融合 ：visible-infrared(title,abstract)；分类 cs.CV

Homogeneous and Heterogeneous Relational Graph for Visible-infrared Person Re-identification

Yujian Feng, Feng Chen, Jian Yu, Yimu Ji, Fei Wu, Shangdong Liu, Xiao-Yuan Jing

专题命中 红外-可见光融合 ：visible-infrared(title,abstract)；分类 cs.CV

Learning by Aligning: Visible-Infrared Person Re-identification using Cross-Modal Correspondences

Hyunjong Park, Sanghoon Lee, Junghyup Lee, Bumsub Ham

专题命中 红外-可见光融合 ：visible-infrared(title,abstract)；分类 cs.CV

Comments iccv 2021

CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification

Chaoyou Fu, Yibo Hu, Xiang Wu, Hailin Shi, Tao Mei, Ran He

专题命中 红外-可见光融合 ：visible-infrared(title,abstract)；分类 cs.CV

Comments Accepted by ICCV 2021

Bridging the Distribution Gap of Visible-Infrared Person Re-identification with Modality Batch Normalization

Wenkang Li, Qi Ke, Wenbin Chen, Yicong Zhou

专题命中 红外-可见光融合 ：visible-infrared(title,abstract)；分类 cs.CV

Unified Batch All Triplet Loss for Visible-Infrared Person Re-identification

Wenkang Li, Ke Qi, Wenbin Chen, Yicong Zhou

专题命中 红外-可见光融合 ：visible-infrared(title,abstract)；分类 cs.CV

Comments 10 pages, 4 figures

SFANet: A Spectrum-aware Feature Augmentation Network for Visible-Infrared Person Re-Identification

Haojie Liu, Shun Ma, Daoxun Xia, Shaozi Li

专题命中 红外-可见光融合 ：visible-infrared(title,abstract)；分类 cs.CV

Comments This paper has been submitted to the journal of IEEE Transactions on Neural Networks and Learning Systems

Dual Gaussian-based Variational Subspace Disentanglement for Visible-Infrared Person Re-Identification

Nan Pu, Wei Chen, Yu Liu, Erwin M. Bakker, Michael S. Lew

专题命中 红外-可见光融合 ：visible-infrared(title,abstract)；分类 cs.CV

Comments Accepted by ACM MM 2020 poster. 12 pages, 10 appendixes

An Efficient Framework for Visible-Infrared Cross Modality Person Re-Identification

Emrah Basaran, Muhittin Gokmen, Mustafa E. Kamasak

专题命中 红外-可见光融合 ：visible-infrared(title,abstract)；分类 cs.CV

Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identification

Mang Ye, Jianbing Shen, David J. Crandall, Ling Shao, Jiebo Luo

专题命中 红外-可见光融合 ：visible-infrared(title,abstract)；分类 cs.CV

Comments Accepted by ECCV20

Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification

Seokeon Choi, Sumin Lee, Youngeun Kim, Taekyung Kim, Changick Kim

专题命中 红外-可见光融合 ：visible-infrared(title,abstract)；分类 cs.CV

Comments Accepted to CVPR 2020

DenseFuse: A Fusion Approach to Infrared and Visible Images

Hui Li, Xiao-Jun Wu

专题命中 红外-可见光融合 ：infrared and visible(title,abstract)；分类 cs.CV

Comments 10 pages, 11 figures, 2 tables. Accepted by IEEE Transactions on Image Processing

A new class of photo-catalytic materials and a novel principle for efficient water splitting under infrared and visible light - MgB2 as unexpected example

V. G. Kravets, A. N. Grigorenko

专题命中 红外-可见光融合 ：infrared and visible(title,abstract)

Near-Infrared and Visible-range Optoelectronics in 2D Hybrid Perovskite/Transition Metal Dichalcogenide Heterostructures

Abin Varghese, Yuefeng Yin, Mingchao Wang, Saurabh Lodha, Nikhil V. Medhekar

专题命中 红外-可见光融合 ：infrared and visible(title,abstract)

Comments 38 pages, main manuscript and supporting information

Journal ref Adv. Mater. Interfaces 2022, 2102174

Broadband and efficient plasmonic control in the near-infrared and visible via strong interference of surface plasmon polaritons

Choon How Gan, Geoffrey R. Nash

专题命中 红外-可见光融合 ：infrared and visible(title,abstract)

High Q micro-ring resonators fabricated from polycrystalline aluminum nitride films for near infrared and visible photonics

Wolfram H. P. Pernice, Chi Xiong, Hong X. Tang

专题命中 红外-可见光融合 ：infrared and visible(title,abstract)

Journal ref Optics Express, Vol. 20, Issue 11, pp. 12261-12269 (2012)

Frequency-Guided Fusion For RGB-Thermal Semantic Segmentation

频率引导的RGB-热红外语义分割融合

İsmail Emre Canıtez, Özgür Erkent

机构 * Hacettepe University（哈切特佩大学） 纠错

专题命中 红外-可见光融合 ：visible-infrared(abstract,abstract_cn)；multi-modal fusion(abstract)；分类 cs.CV

AI总结 提出一种基于双ConvNeXt V2骨干网络的多模态融合架构，通过频率分解和置信门控残差机制融合RGB与热红外特征，在MFNet和PST900上以较低参数量实现先进性能。

Comments 9 pages, 7 figures, To be Presented at Perception Beyond the Visible Spectrum workshop series (IEEE PBVS) at CVPR, 2026

A Unified Solution to Video Fusion: From Multi-Frame Learning to Benchmarking

Zixiang Zhao, Haowen Bai, Bingxin Ke, Yukun Cui, Lilun Deng, Yulun Zhang, Kai Zhang, Konrad Schindler

机构 * ETH Zürich（苏黎世联邦理工学院） ； Xi’an Jiaotong University（西安交通大学） ； Shanghai Jiao Tong University（上海交通大学） ； Nanjing University（南京大学） 纠错

专题命中 红外-可见光融合 ：image fusion(abstract)；multi-focus(abstract)；multi-exposure(abstract)；分类 cs.CV

Comments Accepted by NeurIPS 2025 (Spotlight)

Hierarchical Semantic-Visual Fusion of Visible and Near-infrared Images for Long-range Haze Removal

Yi Li, Xiaoxiong Wang, Jiawei Wang, Yi Chang, Kai Cao, Luxin Yan

机构 * National Key Laboratory of Multispectral Information Intelligent Processing Technology, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology（多光谱信息智能处理技术国家实验室，人工智能与自动化学院，华中科技大学） ； State Key Laboratory of Dynamic Optical Imaging and Measurement（动态光学成像与测量国家重点实验室） 纠错

专题命中 红外-可见光融合 ：multimodal fusion(abstract)；infrared and visible(abstract)；visible-infrared(abstract)；分类 cs.CV

Comments This work has been accepted by IEEE Transactions on Multimedia for publication

Exploring Fusion Strategies for Accurate RGBT Visual Object Tracking

Zhangyong Tang, Tianyang Xu, Hui Li, Xiao-Jun Wu, Xuefeng Zhu, Josef Kittler

专题命中 红外-可见光融合 ：image fusion(abstract)；feature-level fusion(abstract)；decision-level fusion(abstract)；分类 cs.CV

Comments 13 pages, 10 figures

Navigation Around Unknown Space Objects Using Visible-Thermal Image Fusion

利用可见光与热红外图像融合进行未知空间物体的导航

Eric J. Elias, Michael Esswein, Jonathan P. How, David W. Miller

机构 * Draper Scholar, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology（麻省理工学院航空航天系） ； Senior Member of Technical Staff, The Charles Stark Draper Laboratory Inc.（查尔斯·斯塔克·德拉珀实验室公司） ； Ford Professor of Engineering, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology（麻省理工学院航空航天系） ； Professor Post Tenure, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology（麻省理工学院航空航天系） 纠错

专题命中 红外-可见光融合 ：image fusion(title)；分类 cs.CV、cs.RO

AI总结 本文提出利用可见光与热红外图像融合技术，提升在复杂光照条件下对未知空间物体的导航精度。

Comments 18 pages, 11 figures. To be published in proceedings of AIAA SCITECH 2026 Forum

PulmoFusion: Advancing Pulmonary Health with Efficient Multi-Modal Fusion

Ahmed Sharshar, Yasser Attia, Mohammad Yaqub, Mohsen Guizani

专题命中 红外-可见光融合 ：multi-modal fusion(title)；分类 cs.CV、eess.IV

Journal ref (ISBI 2025) 2025 IEEE International Symposium on Biomedical Imaging

SwinFuSR: an image fusion-inspired model for RGB-guided thermal image super-resolution

Cyprien Arnold, Philippe Jouvet, Lama Seoud

专题命中 红外-可见光融合 ：image fusion(title)；分类 cs.CV、eess.IV

Comments Accepted at 20th IEEE Workshop on Perception Beyond the Visible Spectrum, CVPR 2024

HDRT: A Large-Scale Dataset for Infrared-Guided HDR Imaging

Jingchao Peng, Thomas Bashford-Rogers, Francesco Banterle, Haitao Zhao, Kurt Debattista

专题命中 红外-可见光融合 ：multi-modal fusion(abstract)；multi-exposure(abstract)；分类 cs.CV、eess.IV；information fusion(journal_ref)

Journal ref Information Fusion, 120(2025), pp. 103109

Bridging Multimodal Fusion and Expert Routing via Spectral Reliability Descriptors for Robust Object Detection

复用融合时频谱可靠性用于RGB-红外目标检测的自适应融合与专家路由

Yefeng Wu

机构 * Tsinghua University（清华大学） 纠错

专题命中 红外-可见光融合 ：multimodal fusion(title)；分类 cs.CV

AI总结 提出一种无参数的7维频谱可靠性描述符，通过频谱可靠性融合和可靠性条件专家路由，提升RGB-红外目标检测在退化条件下的性能。

Fusion or Confusion? Assessing the impact of visible-thermal image fusion for automated wildlife detection

融合还是混淆？评估可见光-热成像融合对自动化野生动物检测的影响

Camille Dionne-Pierre, Samuel Foucher, Jérôme Théau, Jérôme Lemaître, Patrick Charbonneau, Maxime Brousseau, Mathieu Varin

机构 * Department of Applied Geomatics, Université de Sherbrooke（舍布鲁克大学应用地理信息学系） ； Quebec Centre for Biodiversity Science, McGill University（麦吉尔大学魁北克生物多样性科学中心） ； Ministère de l’Environnement, de la Lutte contre les Changements Climatiques, de la Faune et des Parcs (MELCCFP)（魁北克省环境、气候变化、野生动物和公园部） ； Centre d'enseignement et de recherche en foresterie de Sainte-Foy（圣福瓦林业教学与研究中心） 纠错

专题命中 红外-可见光融合 ：image fusion(title)；分类 cs.CV

AI总结 本文通过大蓝鹭案例研究，评估了可见光与热红外图像融合对自动化野生动物检测的效果，发现融合方法提升了F1分数，但受限于热成像视角和对齐约束。

Comments 19 pages, 9 figures, submitted to Remote Sensing in Ecology and Conservation

UniTriGen: Unified Triplet Generation of Aligned Visible-Infrared-Label for Few-Shot RGB-T Semantic Segmentation

UniTriGen: 一致的可见-红外-标签三元组生成用于少样本RGB-T语义分割

Ping Zhou, Haoyu Wang, Mengmeng Zheng, Lei Zhang, Wei Wei, Chen Ding, Fei Zhou

机构 * School of Computer Science, Northwestern Polytechnical University（西北工业大学计算机学院） ； School of Computer Science & Technology, Xi’an University of Posts & Telecommunications（西安邮电大学计算机科学与技术学院） ； MMLab, The Chinese University of Hong Kong（香港中文大学MMLab） 纠错

专题命中 红外-可见光融合 ：visible-infrared(title)；分类 cs.CV

AI总结 UniTriGen提出统一三元组生成框架，通过共享潜在空间和扩散过程生成一致的可见-红外-标签三元组，解决少样本RGB-T语义分割中的对齐问题。