4 citations · 5 across the 9 of their papers we have counts for
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cs.CV2024
Apollo: An Exploration of Video Understanding in Large Multimodal Models
Orr Zohar, Xiaohan Wang, Yann Dubois +9
Despite the rapid integration of video perception capabilities into Large Multimodal Models (LMMs), the underlying mechanisms driving their video understanding remain poorly unders…
cs.CV2024
Video-STaR: Self-Training Enables Video Instruction Tuning with Any Supervision
Orr Zohar, Xiaohan Wang, Yonatan Bitton +2
The performance of Large Vision Language Models (LVLMs) is dependent on the size and quality of their training datasets. Existing video instruction tuning datasets lack diversity a…
cs.CV2024★ 1 cited
VideoAgent: Long-form Video Understanding with Large Language Model as Agent
Xiaohan Wang, Yuhui Zhang, Orr Zohar +1
Long-form video understanding represents a significant challenge within computer vision, demanding a model capable of reasoning over long multi-modal sequences. Motivated by the hu…