One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos Zechen Bai 1 Tong He2 Haiyang Mei 1 Pichao Wang 2

We introduce VideoLISA, a video-based multimodal large language model designed to tackle the problem of language-instructed reasoning segmentation in videos. Leveraging the reasoning capabilities and world knowledge of large language models, and augmented by the Segment Anything Model, VideoLISA generates temporally consistent segmentation masks in videos based on language instructions.