Methods › Computer Vision › Point Cloud Models › YOHO
You Only Hypothesize Once
YOHO
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
You Only Hypothesize Once is a local descriptor-based framework for the registration of two unaligned point clouds. The proposed descriptor achieves the rotation invariance by recent technologies of group equivariant feature learning, which brings more robustness to point density and noise. The descriptor in YOHO also has a rotation-equivariant part, which enables the estimation the registration from just one correspondence hypothesis.
Papers archive 2025-07-28
4 shown of 4, 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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Single-Image-Based Deep Learning for Segmentation of Early Esophageal Cancer Lesions 9 Jun 2023 · 0 repositories · arXiv:2306.05912
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Evaluating robustness of You Only Hear Once(YOHO) Algorithm on noisy audios in the VOICe Dataset 1 Nov 2021 · 1 repository · arXiv:2111.01205
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You Only Hear Once: A YOLO-like Algorithm for Audio Segmentation and Sound Event Detection 1 Sep 2021 · 1 repository · arXiv:2109.00962
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You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors 1 Sep 2021 · 1 repository · arXiv:2109.00182
Tasks archive 2025-07-28
12 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
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections