InteracVid: Building a Real Interactive Audio-Visual Response Dataset from Live-Chat Videos
Large language models have made text the default medium for human--AI interaction, buttext alone cannot express the full range of responses required by multimodal assistants,avatars, and embodied agents. While recent audio-video generative models can synthesizehigh-fidelity synchronized content, existing supervision is largely \emph{descriptive}:models are trained to render captions rather than to produce audio-visual responsescaused by external user interactions. We introduce \textbf{InteracVid}, \emph{the firstopen-source large-scale dataset that addresses this missing supervision}, so that everysample couples a preceding audio-visual context and an external stimulus with the realintera...
| Authors | Chi Zhang, Haoyang Shi, Yueyi Liu et al. |
|---|---|
| Primary category | cs.CV |
| Published | 2 August 2026 |
| Last updated at source | 2 August 2026 |
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