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ShapeR: Robust Conditional 3D Shape Generation from Casual Captures research paper by Meta, 2026

Meta · Jan 16, 2026 · Multimodal and robotics · 16 citations · 25 upvotes · unverified

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What it shows

ShapeR generates high-fidelity 3D shapes from casual image sequences using visual-inertial SLAM, 3D detection, and vision-language models with rectified flow transformer conditioning.

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

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About this paper
Authors
Yawar Siddiqui, Duncan Frost, Samir Aroudj and 9 more
arXiv
2601.11514 · PDF
Venue
arXiv.org
Citations
16, 2 influential · Semantic Scholar
Upvotes
25 · Hugging Face
Code
github.com/facebookresearch/ShapeR
Lab
Meta · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

What changed
Influential citationsfirst count: 2Sep 25, 2026
Citationsfirst count: 16Sep 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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