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Point2Part: Unified 3D Partitioning from Point Prompts

Paper recorded by Signals 4 on 2026-09-29 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-29 on arXiv · recorded by Signals 4 on 2026-09-30

Category: cs.CV · 计算机视觉 · first seen 2026-09-30

Abstract

Existing 3D part decomposition methods do not necessarily partition the original shape into non-overlapping parts that collectively cover the entire shape, allowing overlaps or gaps that hinder downstream part-level applications. We instead formulate part decomposition as a joint partitioning of the entire shape, where the predicted parts are non-overlapping and jointly recover the entire shape. O

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#1 most recent of 357 cs.CV papers we have recorded · ↓ older: Counterfactual Video Generation Enables Scalable Humanoid Loco-Manipul
Cite this page: Point2Part: Unified 3D Partitioning from Point Prompts: the #1 most recent of 357 cs.CV papers we have recorded (as of 2026-09-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/point2part-unified-3d-partitioning-from-point-prompts.html
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