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PhD Proposal: Towards Effective Temporal Modeling for Video Understanding and Beyond
Bo He
Wednesday, January 18, 2023, 3:00-5:00 pm Calendar
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ideo understanding is a fundamental research topic in computer vision, which requires extracting and analyzing information from videos automatically. Compared to the image modality, the video modality significantly differs from it with additional temporal dependencies, which provide crucial clues to help understand what happens across time. Therefore, how to effectively model temporal relationships for videos is of vital importance for video understanding.

This thesis is divided into two parts. In the first part, we mainly concentrate on how to model the temporal dependencies for different video understanding tasks, including action recognition, temporal action localization, and video summarization. In the second part, beyond the pure understanding of video content, we focus on how to represent large-scale videos compactly and efficiently. We propose to encode diverse videos into a single neural network and explore its superior advantages in various video downstream tasks.
Examining Committee


Dr. Abhinav Shrivastava

Department Representative:

Dr. Ramani Duraiswami


Dr. Furong Huang


Dr. Chen Sun


Bo He is a PhD student at the University of Maryland, College Park, advised by Prof. Abhinav Shrivastava. His research interests lie in video understanding, video neural representation and multimodal learning. He received the B.Eng. degree in Computer Science and Technology from the University of Chinese Academy of Sciences.

This talk is organized by Tom Hurst