Contrastive Action-Image Pre-training for Visuomotor Control
Existing vision encoders for robotics face a fundamental bottleneck: robotic datasets lack the scale necessary for large-scale pre-training. Prior work circumvents this data scarcity by turning to internet-scale image and language data or egocentric human video. While these models show promise, neither paradigm learns from paired vision and action data, which downstream visuomotor control policies require. However, robot trajectories, the most direct source of this paired signal, are not available at pre-training scale, motivating us to extract action signals from abundant human video instead. To this end, we introduce CAIP (Contrastive Action-Image Pre-training), a vision encoder that tr...
| Authors | Yuvan Sharma, Dantong Niu, Anirudh Pai et al. |
|---|---|
| Primary category | cs.RO |
| Published | 15 June 2026 |
| Last updated at source | 15 June 2026 |
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