May 14, 2024, 4:46 a.m. | Yuanyuan Jiang, Jianqin Yin

cs.CV updates on

arXiv:2405.07451v1 Announce Type: new
Abstract: While vision-language pretrained models (VLMs) excel in various multimodal understanding tasks, their potential in fine-grained audio-visual reasoning, particularly for audio-visual question answering (AVQA), remains largely unexplored. AVQA presents specific challenges for VLMs due to the requirement of visual understanding at the region level and seamless integration with audio modality. Previous VLM-based AVQA methods merely used CLIP as a feature encoder but underutilized its knowledge, and mistreated audio and video as separate entities in a dual-stream …

abstract arxiv audio challenges clip excel fine-grained integration language multimodal network pretrained models question question answering reasoning seamless integration tasks type understanding vision vision-language visual vlms while

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