SOURCE-LINKED INTELLIGENCE
PRISM: Predictive Recomposition via Semantic Latent Decomposition for View-invariant Video Representation Learning
Cross-view video representation learning aims to capture viewpoint-invariant action semantics despite substantial appearance changes across egocentric and exocentric videos. However, existing methods encode each video as a unified embedding, where view-invariant and view-variant semantics inevitably entangle under co-occurrences - a failure mode we show persists even in cross-view methods explicitly trained for view-invariance. Our key insight is that a view-invariant feature is truly disentangled when it can be sufficiently recomposed with an arbitrary view-variant feature while preserving th
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-31T07:43:02.000Z
First collected: 2026-09-21T07:01:58.596Z. This is not the publication date.