Chenglei Peng

Papers

Total Citations

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About

Chenglei Peng is a rising researcher in computer vision, with a primary focus on human action detection and anticipation in videos. His most-cited work, the comprehensive survey "Online human action detection and anticipation in videos: A survey" (2022), has already garnered 34 citations, establishing him as a key voice in this rapidly evolving field. This survey systematically maps the landscape of online action understanding—a critical challenge for applications in autonomous driving, surveillance, and human-robot interaction—by categorizing methods, datasets, and evaluation protocols. Peng’s contribution lies in synthesizing fragmented research into a coherent framework, identifying open problems such as real-time processing and long-term anticipation, and providing a roadmap for future work. His ability to distill complex technical trends into accessible insights makes this survey an essential resource for students and researchers entering the domain. As his citation count grows, Peng’s work signals a promising trajectory in advancing how machines perceive and predict human behavior in dynamic, unconstrained environments.