Advancing Complex Video Object Segmentation via Progressive Concept Construction

Researchers introduce Segment Concept (SeC), a new video object segmentation framework that uses Large Vision-Language Models to build conceptual representations rather than relying on traditional feature matching. SeC achieves an 11.8-point improvement over SAM 2.1 on the new SeCVOS benchmark, establishing state-of-the-art performance in concept-aware video object segmentation.