SAVE: Speech-Aware Video Representation Learning for Video-Text Retrieval
For video-text retrieval, the use of CLIP has been a de facto choice. Since CLIP provides only image and text encoders, this consensus has led to a biased paradigm that entirely ignores the sound track of videos. While several attempts have been made to reintroduce audio -- typically by incorporating an audio encoder and fusing its output with visual features -- these methods face two challenges: ineffective representation of speech content and suboptimal vision-audio fusion. To address these issues jointly, we propose SAVE, a Speech Aware Video rEpresentation learning method. SAVE improves upon AVIGATE, a SOTA audiovisual method, with a dedicated speech branch for more effective speech e...
| Authors | Ruixiang Zhao, Zhihao Xu, Bangxiang Lan et al. |
|---|---|
| Primary category | cs.CV |
| Published | 9 March 2026 |
| Last updated at source | 11 March 2026 |
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