Jingzhao Dai

Papers

Total Citations

H-Index

About

Jingzhao Dai is a researcher specializing in computer vision and video understanding, with a particular focus on human action detection and anticipation. His most-cited work, the 2022 survey "Online human action detection and anticipation in videos," has garnered 34 citations, establishing him as a key contributor to this rapidly evolving field. This comprehensive survey systematically reviews state-of-the-art methods for recognizing and predicting human actions in real-time video streams, addressing critical challenges such as temporal modeling, online inference, and the integration of detection with anticipation. By synthesizing diverse approaches and identifying open problems, Dai's work provides an essential roadmap for researchers aiming to develop systems that can understand and forecast human behavior in dynamic environments. His contributions are particularly relevant for applications in surveillance, human-robot interaction, and autonomous driving, where timely and accurate action recognition is paramount. Through his survey, Dai has helped shape the direction of online video analysis, offering both a foundational reference and a catalyst for future innovation in this exciting area of artificial intelligence.