most citedMeViS: A Multi-Modal Dataset for Referring Motion Expression Video Segmentation

13 citations · 13 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CV2026

SAM3-DMS: Decoupled Memory Selection for Multi-target Video Segmentation of SAM3

Ruiqi Shen, Chang Liu, Henghui Ding

Segment Anything 3 (SAM3) has established a powerful foundation that robustly detects, segments, and tracks specified targets in videos. However, in its original implementation, it…

cs.CV202513 cited

MeViS: A Multi-Modal Dataset for Referring Motion Expression Video Segmentation

Henghui Ding, Chang Liu, Shuting He +4

This paper proposes a large-scale multi-modal dataset for referring motion expression video segmentation, focusing on segmenting and tracking target objects in videos based on lang…

cs.CV2025

Segment Anything Across Shots: A Method and Benchmark

Hengrui Hu, Kaining Ying, Henghui Ding

This work focuses on multi-shot semi-supervised video object segmentation (MVOS), which aims at segmenting the target object indicated by an initial mask throughout a video with mu…

cs.CV2025

LSVOS 2025 Challenge Report: Recent Advances in Complex Video Object Segmentation

Chang Liu, Henghui Ding, Kaining Ying +46

This report presents an overview of the 7th Large-scale Video Object Segmentation (LSVOS) Challenge held in conjunction with ICCV 2025. Besides the two traditional tracks of LSVOS…

cs.CV2025

MOSEv2: A More Challenging Dataset for Video Object Segmentation in Complex Scenes

Henghui Ding, Kaining Ying, Chang Liu +5

Video object segmentation (VOS) aims to segment specified target objects throughout a video. Although state-of-the-art methods have achieved impressive performance (e.g., 90+% J&F)…

cs.CV2025

Multimodal Referring Segmentation: A Survey

Henghui Ding, Song Tang, Shuting He +3

Multimodal referring segmentation aims to segment target objects in visual scenes, such as images, videos, and 3D scenes, based on referring expressions in text or audio format. Th…