Unraveling Instance Associations: A Closer Look for Audio-Visual Segmentation

arXiv:2304.02970v5 Announce Type: replace
Abstract: Audio-visual segmentation (AVS) is a challenging task that involves accurately segmenting sounding objects based on audio-visual cues. The effectiveness of audio-visual learning critically depends on achieving accurate cross-modal alignment between sound and visual objects. Successful audio-visual learning requires two essential components: 1) a challenging dataset with high-quality pixel-level multi-class annotated images associated with audio files, and 2) a model that can establish strong links between audio information and its corresponding visual object. However, these requirements …

abstract alignment arxiv audio avs closer look components cs.cv cs.mm dataset instance look modal objects segmentation sound type visual visual cues