Action Detection
Action detection in videos focuses on identifying and precisely locating actions within video streams, addressing challenges like cluttered scenes and varying action durations. Current research emphasizes the development of robust and efficient models, often employing transformer architectures and incorporating multi-modal data (RGB, depth, audio, skeleton data) to improve accuracy and handle diverse action types. This field is crucial for various applications, including sports analytics, educational research, and surveillance systems, driving advancements in video understanding and enabling the development of AI-driven tools for diverse sectors.
Papers
Bodily Behaviors in Social Interaction: Novel Annotations and State-of-the-Art Evaluation
Michal Balazia, Philipp Müller, Ákos Levente Tánczos, August von Liechtenstein, François Brémond
P2ANet: A Dataset and Benchmark for Dense Action Detection from Table Tennis Match Broadcasting Videos
Jiang Bian, Xuhong Li, Tao Wang, Qingzhong Wang, Jun Huang, Chen Liu, Jun Zhao, Feixiang Lu, Dejing Dou, Haoyi Xiong