Revisiting Anchor Mechanisms for Temporal Action Localization
School of Automation, Northwestern Polytechnical University（西北工业大学自动化学院）；School of Mechano-Electronic Engineering, Xidian University（西安电子科技大学机电工程学院）；Microsoft Research Asia（微软亚洲研究院）
Le Yang, Houwen Peng, Dingwen Zhang, Jianlong Fu, Junwei Han
Most of the current action localization methods follow an anchor-based pipeline: depicting action instances by pre-defined anchors, learning to select the anchors closest to the ground truth, and predicting the confidence of anchors with refinements. Pre-defined anchors set prior about the location and duration for action instances, which facilitates the localization for common action instances but limits the flexibility for tackling action instances with drastic varieties, especially for extremely short or extremely long ones. To address this problem, this paper proposes a novel anchor-free action localization module that assists action localization by temporal points. Specifically, this module represents an action instance as a point with its distances to the starting boundary and ending boundary, alleviating the pre-defined anchor restrictions in terms of action localization and duration. The proposed anchor-free module is capable of predicting the action instances whose duration is either extremely short or extremely long. By combining the proposed anchor-free module with a conventional anchor-based module, we propose a novel action localization framework, called A2Net. The cooperation between anchor-free and anchor-based modules achieves superior performance to the state-of-the-art on THUMOS14 (45.5% vs. 42.8%). Furthermore, comprehensive experiments demonstrate the complementarity between the anchor-free and the anchor-based module, making A2Net simple but effective.
Revisiting Foreground and Background Separation in Weakly-supervised Temporal Action Localization: A Clustering-based Approach
University of Science and Technology of China（中国科学技术大学）；Institute of Artificial Intelligence, Hefei Comprehensive National Science Center（合肥综合性国家科学中心人工智能研究院）
Revisiting Feature Alignment for One-stage Object Detection
University of Chinese Academy of Sciences（中国科学院大学）；Center for Research on Intelligent Perception and Computing, CASIA（中国科学院自动化研究所智能感知与计算研究中心）；TuSimple（图森未来）；Center for Excellence in Brain Science and Intelligence Technology, CAS（中国科学院脑科学与智能技术卓越创新中心）
Grounding Emotion Recognition with Visual Prototypes: VEGA -- Revisiting CLIP in MERC
Xi'an Jiaotong University（西安交通大学）；Queen Mary University of London（伦敦女王玛丽大学）；Center for Multimodal AI（多模态人工智能中心）；Digital Environment Research Institute（数字环境研究院）
Consistency-Aware Anchor Pyramid Network for Crowd Localization
University of Chinese Academy of Science（中国科学院大学）；Australian Institute for Machine Learning, The University of Adelaide（阿德莱德大学澳大利亚机器学习研究所）；Peng Cheng Laboratory（鹏城实验室）；University of California, Merced（加州大学默塞德分校）；University of Trento（特伦托大学）
Scope Head for Accurate Localization in Object Detection
The University of Sydney（悉尼大学）；SenseTime Computer Vision Research Group（商汤科技计算机视觉研究组）；University of Oxford（牛津大学）；Shanghai Jiao Tong University（上海交通大学）；SenseTime Group Ltd（商汤集团有限公司）；The University of Adelaide（阿德莱德大学）
National University of Singapore（新加坡国立大学）；Nanjing University of Posts and Telecommunications（南京邮电大学）；Qilu University of Technology (Shandong Academy of Sciences)（齐鲁工业大学（山东科学院））
Boundary Proposal Network for Two-Stage Natural Language Video Localization
Zhejiang University（浙江大学）；Tencent AI Lab（腾讯人工智能实验室）；University of Rochester（罗切斯特大学）；National University of Singapore（新加坡国立大学）；Zhejiang University of Science and Technology（浙江科技大学）
Learning to Anchor Visual Odometry: KAN-Based Pose Regression for Planetary Landing
University of Chinese Academy of Sciences（中国科学院大学）；Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences（中国科学院空间利用技术与工程中心）
Interpretable Vertebral Fracture Quantification via Anchor-Free Landmarks Localization
IRA Labs Ltd（IRA实验室有限公司）；Skolkovo Institute of Science and Technology（斯科尔科沃科学技术学院）；Kharkevich Institute for Information Transmission Problems（哈尔克维奇信息传输问题研究所）；Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department（莫斯科卫生部诊断与远程医疗技术研究实践临床中心）；Osimis SA（Osimis股份公司）；Artificial Intelligence Research Institute（人工智能研究所）
