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

arXiv 2507.09459 ↗First posted 13 Jul 2025cs.CV cs.ROcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 25 of its 34 references that are in the map. First posted on arXiv 13 Jul 2025.

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25 of 34 references.

References · 25

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2017Graph Attention Networkscited by 8,854
  3. 2017Inductive Representation Learning on Large Graphscited by 6,284
  4. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  5. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
  6. 2015FaceNet: A Unified Embedding for Face Recognition and Clusteringcited by 2,833
  7. 2018Dynamic Graph CNN for Learning on Point Cloudscited by 2,220
  8. 2021Align before Fuse: Vision and Language Representation Learning with Momentum Distillationcited by 1,612
  9. 2020Point Transformercited by 1,462
  10. 2019KPConv: Flexible and Deformable Convolution for Point Cloudscited by 1,202
  11. 2017Multimodal Machine Learning: A Survey and Taxonomycited by 1,004
  12. 2018PointConv: Deep Convolutional Networks on 3D Point Cloudscited by 656
13 more
  1. 2019Multimodal Transformer for Unaligned Multimodal Language Sequencescited by 637
  2. 2019RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Cloudscited by 584
  3. 2021Neural Fields in Visual Computing and Beyondcited by 539
  4. 2021PointCLIP: Point Cloud Understanding by CLIPcited by 461
  5. 2017Joint 2D-3D-Semantic Data for Indoor Scene Understandingcited by 404
  6. 2022Point Transformer V2: Grouped Vector Attention and Partition-based Poolingcited by 384
  7. 2021Vector Neurons: A General Framework for SO(3)-Equivariant Networkscited by 304
  8. 2022Mask3D: Mask Transformer for 3D Semantic Instance Segmentationcited by 299
  9. 2021PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Cloudscited by 211
  10. 2017Multi-view Supervision for Single-view Reconstruction via Differentiable Ray Consistencycited by 177
  11. 2017SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentationcited by 168
  12. 2019Grid-GCN for Fast and Scalable Point Cloud Learningcited by 103
  13. 20193D Instance Segmentation via Multi-Task Metric Learningcited by 79

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