SegVec3D: A Method for Vector Embedding of 3D Objects Oriented Towards Robot manipulation

• URL: http://arxiv.org/abs/2507.09459v1
• Date: Sun, 13 Jul 2025 02:54:55 GMT
• Title: SegVec3D: A Method for Vector Embedding of 3D Objects Oriented Towards Robot manipulation
• Authors: Zhihan Kang, Boyu Wang,
• Abstract summary: SegVec3D is a novel framework for 3D point cloud instance segmentation.<n>It integrates attention mechanisms, embedding learning, and cross-modal alignment.
• Score: 4.19191792860075
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We propose SegVec3D, a novel framework for 3D point cloud instance segmentation that integrates attention mechanisms, embedding learning, and cross-modal alignment. The approach builds a hierarchical feature extractor to enhance geometric structure modeling and enables unsupervised instance segmentation via contrastive clustering. It further aligns 3D data with natural language queries in a shared semantic space, supporting zero-shot retrieval. Compared to recent methods like Mask3D and ULIP, our method uniquely unifies instance segmentation and multimodal understanding with minimal supervision and practical deployability.

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