RESEARCH PAPER
V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learning
Classification
View four quadrants- Major category
- Components of WAMs
- Quadrant
- Not applicable
- Architecture
- Not applicable
- Prediction paradigm
- Not applicable
- Subcategories
- Visual encoders & representations
- Source review status
- Verified from primary sources
Category review. V-JEPA 2.1 supplies general self-supervised dense image/video representations. Its context/EMA-target encoders and multilayer latent prediction are reusable perception features; task heads and planning world models are separate downstream adaptations. Its 2026 date does not disqualify a genuine representation component. Reading evidence
Contribution
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Abstract
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