13 citations · 13 across the 5 of their papers we have counts for
6 papers
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…
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…
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…
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)…
Towards Omnimodal Expressions and Reasoning in Referring Audio-Visual Segmentation
Kaining Ying, Henghui Ding, Guangquan Jie +1
Referring audio-visual segmentation (RAVS) has recently seen significant advancements, yet challenges remain in integrating multimodal information and deeply understanding and reas…
MOVE: Motion-Guided Few-Shot Video Object Segmentation
Kaining Ying, Hengrui Hu, Henghui Ding
This work addresses motion-guided few-shot video object segmentation (FSVOS), which aims to segment dynamic objects in videos based on a few annotated examples with the same motion…