1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2025
VEU-Bench: Towards Comprehensive Understanding of Video Editing
Bozheng Li, Yongliang Wu, Yi Lu +7
Widely shared videos on the internet are often edited. Recently, although Video Large Language Models (Vid-LLMs) have made great progress in general video understanding tasks, thei…
cs.CV2024★ 1 cited
VideoGLaMM: A Large Multimodal Model for Pixel-Level Visual Grounding in Videos
Shehan Munasinghe, Hanan Gani, Wenqi Zhu +4
Fine-grained alignment between videos and text is challenging due to complex spatial and temporal dynamics in videos. Existing video-based Large Multimodal Models (LMMs) handle bas…
cs.CV2024
CLIP-VIS: Adapting CLIP for Open-Vocabulary Video Instance Segmentation
Wenqi Zhu, Jiale Cao, Jin Xie +2
Open-vocabulary video instance segmentation strives to segment and track instances belonging to an open set of categories in a videos. The vision-language model Contrastive Languag…