UniPart: Towards Zero-shot Language-Grounded 3D Part Segmentation for Embodied Interaction
Paper recorded by Signals 4 on 2026-09-11 in cs.CV. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-11 on arXiv · recorded by Signals 4 on 2026-09-14
Category: cs.CV · 计算机视觉 · first seen 2026-09-14
Abstract
Fine-grained robotic manipulation depends on understanding parts, not only whole objects. Existing 3D foundation models tend to be either generalized but object-aware, or part-aware but limited to closed-set taxonomies, which weakens zero-shot transfer. We study text-conditioned 3D part segmentation, where a free-form phrase selects a functional part on point cloud. We introduce UniPart, a feed-fo
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Cite this page: UniPart: Towards Zero-shot Language-Grounded 3D Part Segmentation for Embodied Interaction: the #72 most recent of 237 cs.CV papers we have recorded (as of 2026-09-11). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/unipart-towards-zero-shot-language-grounded-3d-part-segmentation-for-embodied-in.html
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