1 citations · 1 across the 6 of their papers we have counts for
6 papers
Segmentation before Answering: Pixel Grounding for MLLM Visual Reasoning
Yake Wei, Yuan Wang, Fengyun Rao +2
Recent advancements in Multimodal Large Language Models (MLLMs) have evolved from static perception to interleaved visual-language reasoning, often referred to as ``thinking with i…
Crab: A Scalable and Unified Audio-Visual Scene Understanding Model with Explicit Cooperation
Dongnuan Cai, Henghui Du, Chang Zhou +5
Developing Audio-Visual Large Language Models (AV-LLMs) for unified scene understanding is pivotal in multimodal intelligence. While instruction tuning enables pre-trained models w…
Unveiling and Mitigating Bias in Audio Visual Segmentation
Peiwen Sun, Honggang Zhang, Di Hu
Community researchers have developed a range of advanced audio-visual segmentation models aimed at improving the quality of sounding objects' masks. While masks created by these mo…
Ref-AVS: Refer and Segment Objects in Audio-Visual Scenes
Yaoting Wang, Peiwen Sun, Dongzhan Zhou +3
Traditional reference segmentation tasks have predominantly focused on silent visual scenes, neglecting the integral role of multimodal perception and interaction in human experien…
Can Textual Semantics Mitigate Sounding Object Segmentation Preference?
Yaoting Wang, Peiwen Sun, Yuanchao Li +2
The Audio-Visual Segmentation (AVS) task aims to segment sounding objects in the visual space using audio cues. However, in this work, it is recognized that previous AVS methods sh…
Stepping Stones: A Progressive Training Strategy for Audio-Visual Semantic Segmentation
Juncheng Ma, Peiwen Sun, Yaoting Wang +1
Audio-Visual Segmentation (AVS) aims to achieve pixel-level localization of sound sources in videos, while Audio-Visual Semantic Segmentation (AVSS), as an extension of AVS, furthe…