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V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learning research paper by Meta, 2026

Meta · Mar 15, 2026 · Multimodal and robotics · 83 citations · 39 upvotes · unverified

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What it shows

V-JEPA 2.1 is a self-supervised model that learns dense visual representations for images and videos through a combination of dense predictive loss, deep self-supervision, multi-modal tokenizers, and effective scaling.

UnverifiedHugging Face's summary; not yet checked by hand.

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About this paper
Authors
Lorenzo Mur-Labadia, Matthew Muckley, Amir Bar and 6 more
arXiv
2603.14482 · PDF
Venue
arXiv.org
Citations
83, 37 influential · Semantic Scholar
Upvotes
39 · Hugging Face
Lab
Meta · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

What changed
Influential citationsfirst count: 37Sep 25, 2026
Citationsfirst count: 83Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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