Summary of Av-link: Temporally-aligned Diffusion Features For Cross-modal Audio-video Generation, by Moayed Haji-ali et al.
AV-Link: Temporally-Aligned Diffusion Features for Cross-Modal Audio-Video Generation
by Moayed Haji-Ali, Willi Menapace, Aliaksandr Siarohin, Ivan Skorokhodov, Alper Canberk, Kwot Sin Lee, Vicente Ordonez, Sergey Tulyakov
First submitted to arxiv on: 19 Dec 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG); Sound (cs.SD); Audio and Speech Processing (eess.AS)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes AV-Link, a unified framework for Video-to-Audio (A2V) and Audio-to-Video (A2V) generation that leverages frozen video and audio diffusion models. The framework uses a Fusion Block to facilitate bidirectional information exchange between the two modalities through temporally-aligned self attention operations. Unlike prior work, AV-Link achieves both tasks in a single framework using features from the complementary modality. The paper demonstrates significant improvements in audio-video synchronization compared to more expensive baselines like MovieGen. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary AV-Link is a new way to turn videos into audio and vice versa. It’s like having a magic translator that understands both languages! Scientists created this system by combining information from frozen video and audio models. This allows AV-Link to translate between the two in one go, without needing separate systems for each direction. The results show that AV-Link does a much better job of matching up the audio and video than other methods. |
Keywords
» Artificial intelligence » Diffusion » Self attention
