arXiv Computer Vision
6d ago

Semantic-Critical Regions for Video-to-Audio Generation

The paper introduces SCR-V2A, a video-to-audio generation framework that focuses on Semantic-Critical Regions (SCRs)—localized visual cues directly related to sound events. SCR-V2A first identifies these regions via sound-related visual localization, then encodes them with an adapter-based dual visual encoder to produce a control representation that captures both global context and fine-grained sound evidence. This representation conditions an audio generation model, and experiments on in-domain and out-of-domain benchmarks show improved distribution matching and audio quality with few trainable parameters.

By Yun Fang, Wei Guo, Zhuonan Liang, Heng Wang, Weidong Cai
arXiv Computer Vision
4d ago

Frequency-Domain Decomposition and Recomposition for Robust Audio-Visual Segmentation

The paper introduces Frequency-Aware Audio-Visual Segmentation (FAVS), a framework that treats audio-visual segmentation as a frequency-domain decomposition and recomposition task. It comprises a Frequency-Domain Enhanced Decomposer (FDED) that iteratively separates modality-specific semantics and structural features, and a Synergistic Cross-Modal Consistency (SCMC) module that uses a mixture-of-experts architecture to maintain semantic consistency and preserve modality-specific features. Experiments on three benchmark datasets show that FAVS achieves state-of-the-art performance, with qualitative visualizations supporting the effectiveness of both modules.

By Kai Peng, Yunzhe Shen, Miao Zhang, Jia Wang, Leiye Liu, Wei Ji, Jingjing Li, Yongri Piao, Huchuan Lu