13 citations · 13 across the 5 of their papers we have counts for
8 papers
Seek to Segment: Active Perception for Panoramic Referring Segmentation
Song Tang, Shuming Hu, Xincheng Shuai +2
Existing referring segmentation models passively process static images captured from fixed perspectives, limiting their applicability in Embodied AI, where agents must perform acti…
Unison: Benchmarking Unified Multimodal Models via Synergistic Understanding and Generation
Jinyu Liu, Xincheng Shuai, Henghui Ding +1
Unified multimodal models capable of both understanding and generation have achieved remarkable strides. However, despite their unified designs, existing evaluations typically asse…
ROSE: Retrieval-Oriented Segmentation Enhancement
Song Tang, Guangquan Jie, Henghui Ding +1
Existing segmentation models based on multimodal large language models (MLLMs), such as LISA, often struggle with novel or emerging entities due to their inability to incorporate u…
GREx: Generalized Referring Expression Segmentation, Comprehension, and Generation
Henghui Ding, Chang Liu, Shuting He +2
Referring Expression Segmentation (RES) and Comprehension (REC) respectively segment and detect the object described by an expression, while Referring Expression Generation (REG) g…
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…
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)…
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…
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…