Methods › Computer Vision › 6D Pose Estimation Models › PO3D-VQA
Parts, Poses, and Occlusions in 3D Visual Question Answering
PO3D-VQA
Introduced by Xingrui Wang et al. in 3D-Aware Visual Question Answering about Parts, Poses and Occlusions
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
A VQA model that marries two powerful ideas: probabilistic neural symbolic program execution for reasoning and a deep neural network with 3D generative representations of objects for robust visual scene parsing.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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3D-Aware Visual Question Answering about Parts, Poses and Occlusions 27 Oct 2023 · 2 repositories · arXiv:2310.17914Syntology ran 11 of 28 samples · 17 unverified · 14 pointer-only (licence)
Tasks archive 2025-07-28
3 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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