20 citations · 31 across the 11 of their papers we have counts for
4 papers · 1 filter
One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos
Zechen Bai, Tong He, Haiyang Mei +6
We introduce VideoLISA, a video-based multimodal large language model designed to tackle the problem of language-instructed reasoning segmentation in videos. Leveraging the reasoni…
VideoLLM-MoD: Efficient Video-Language Streaming with Mixture-of-Depths Vision Computation
Shiwei Wu, Joya Chen, Kevin Qinghong Lin +7
A well-known dilemma in large vision-language models (e.g., GPT-4, LLaVA) is that while increasing the number of vision tokens generally enhances visual understanding, it also sign…
Learning Video Context as Interleaved Multimodal Sequences
Kevin Qinghong Lin, Pengchuan Zhang, Difei Gao +6
Narrative videos, such as movies, pose significant challenges in video understanding due to their rich contexts (characters, dialogues, storylines) and diverse demands (identify wh…
VideoLLM-online: Online Video Large Language Model for Streaming Video
Joya Chen, Zhaoyang Lv, Shiwei Wu +7
Recent Large Language Models have been enhanced with vision capabilities, enabling them to comprehend images, videos, and interleaved vision-language content. However, the learning…