While motion has garnered attention in various tasks, its potential as a modality for weakly-supervised object detection (WSOD) in static images remains unexplored. Our study introduces an approach to enhance WSOD methods by integrating motion information. This method involves leveraging hallucinated motion from static images to improve WSOD on image datasets, utilizing a Siamese network for enhanced representation learning with motion, addressing camera motion through motion normalization, and selectively training images based on object motion. Experimental validation on the COCO and YouTube-BB datasets demonstrates improvements over a state-of-the-art method.
Pixel-Level Domain Adaptation: A New Perspective for Enhancing Weakly Supervised Semantic Segmentation
Beihang University（北京航空航天大学）；State Key Laboratory of Virtual Reality Technology and Systems（虚拟现实技术与系统国家重点实验室）；School of Computer Science and Engineering（计算机科学与工程学院）；Hangzhou Innovation Institute, Beihang University（北京航空航天大学杭州创新研究院）
Context Patch Fusion With Class Token Enhancement for Weakly Supervised Semantic Segmentation
School of Cyber Science and Engineering, Wuxi University（网络安全科学与工程学院，无锡大学）；School of Informatics, Xiamen University（信息学院，厦门大学）；School of Computer Science, University of Liverpool（计算机科学学院，利物浦大学）
Adaptive Patch Contrast for Weakly Supervised Semantic Segmentation
Xi’an Jiaotong-Liverpool University（西交利物浦大学）；University of Liverpool（利物浦大学）；University of Aberdeen（阿伯丁大学）；Microsoft（微软公司）；Jiangsu United Vocational and Technical College（江苏联合职业技术学院）
Separate and Conquer: Decoupling Co-occurrence via Decomposition and Representation for Weakly Supervised Semantic Segmentation
Academy for Engineering and Technology, Fudan University（复旦大学工程技术学院）；Digital Medical Research Center, School of Basic Medical Sciences, Fudan University（复旦大学基础医学院数字医学研究中心）；Shandong Computer Science Center (National Supercomputer Center in Jinan)（山东计算中心（国家济南超级计算中心））
FedLPPA: Learning Personalized Prompt and Aggregation for Federated Weakly-supervised Medical Image Segmentation
Southern University of Science and Technology (SUSTech)（南方科技大学）；Jiaxing Research Institute, Southern University of Science and Technology（南方科技大学嘉兴研究院）；the University of Hong Kong（香港大学）；the Hong Kong University of Science and Technology（香港科技大学）
3D Weakly Supervised Semantic Segmentation via Class-Aware and Geometry-Guided Pseudo-Label Refinement
College of Computer Science, Beihang University（北京航空航天大学计算机科学学院）；College of Computer Science and Software Engineering, Shenzhen University（深圳大学计算机科学与软件工程学院）；Department of Information Engineering and Computer Science, University of Trento（特伦托大学信息工程与计算机科学系）；Meituan（美团）
Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation
CMIC, Shanghai Jiao Tong University（上海交通大学CMIC）；Beijing Institute of Technology（北京理工大学）；National University of Defense Technology（国防科技大学）；CUHK（香港中文大学）；Shanghai AI Laboratory（上海人工智能实验室）
Supervision-by-Hallucination-and-Transfer: A Weakly-Supervised Approach for Robust and Precise Facial Landmark Detection
School of Information Engineering, Zhongnan University of Economics（经济法律大学信息工程学院）；College of Computer Science and Software Engineering, Shenzhen University（深圳大学计算机科学与软件工程学院）；School of Information Science and Engineering, Yunnan University（云南大学信息科学与工程学院）
Enhancing Weakly Supervised Multimodal Video Anomaly Detection through Text Guidance
School of Computer Science and Technology, Hangzhou Dianzi University（杭州电子科技大学计算机科学与技术学院）；Alibaba Cloud（阿里云）；College of Information Science and Electronic Engineering, Zhejiang University（浙江大学信息科学与电子工程学院）
EAR: Enhancing Uni-Modal Representations for Weakly Supervised Audio-Visual Video Parsing
School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications（智能工程与自动化学院，北京邮电大学）；State Grid Corporation of China（国家电网公司）；School of Artificial Intelligence, Beijing University of Posts and Telecommunications（人工智能学院，北京邮电大学）
CAMEL2: Enhancing weakly supervised learning for histopathology images by incorporating the significance ratio
Multiscale Research Institute of Complex Systems, Fudan University（复旦大学复杂系统多尺度研究院）；Zhangjiang Fudan International Innovation Center, Fudan University（复旦大学张江复旦国际创新中心）；Shanghai AI Laboratory（上海人工智能实验室）；Thorough Lab, Thorough Future（透彻未来实验室）；China-Japan Friendship Hospital（中日友好医院）；Minjiang University（闽江学院）；Peking University（北京大学）；Xiamen University of Technology（厦门理工学院）；Chinese PLA General Hospital（中国人民解放军总医院）
Weakly Supervised Visible-Infrared Person Re-Identification via Heterogeneous Expert Collaborative Consistency Learning
Faculty of Information Engineering and Automation, Kunming University of Science and Technology（昆明理工大学信息工程与自动化学院）；School of Computer Science and Technology, Harbin Institute of Technology（哈尔滨工业大学计算机科学与技术学院）
Beyond Euclidean: Dual-Space Representation Learning for Weakly Supervised Video Violence Detection
Chongqing University of Posts and Telecommunications（重庆邮电大学）；Chongqing Institute for Brain and Intelligence（重庆脑与智能研究院）；Guangyang Bay Laboratory（广阳湾实验室）
D2-Net: Weakly-Supervised Action Localization via Discriminative Embeddings and Denoised Activations
Inception Institute of Artificial Intelligence（启元人工智能研究院）；Mohamed Bin Zayed University of AI（穆罕默德·本·扎耶德人工智能大学）；Monash University（莫纳什大学）；Linköping University（林雪平大学）；University of California Merced（加州大学默塞德分校）；Google Research（谷歌研究院）；Yonsei University（延世大学）
DDG-Net: Discriminability-Driven Graph Network for Weakly-supervised Temporal Action Localization
Beijing University of Posts and Telecommunications（北京邮电大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Centre for Artificial Intelligence and Robotics, HKISI_CAS（中国科学院香港创新研究院人工智能与机器人创新中心）；University of Chinese Academy of Sciences（中国科学院大学）
CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images
School of Physics, Peking University（北京大学物理学院）；School of Computer Science, Peking University（北京大学计算机学院）；Department of Radiotherapy, Peking University Cancer Hospital（北京大学肿瘤医院放疗科）；Department of Radiation Oncology, Peking University Third Hospital（北京大学第三医院放疗科）
