mlsanityData to 7 Oct 2026

Leveraging 2D-VLM for Label-Free 3D Segmentation in Large-Scale Outdoor Scene Understanding

arXiv 2601.02029 ↗First posted 5 Jan 2026cs.CVcited by 0

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Abstract (arXiv)

This paper presents a novel 3D semantic segmentation method for large-scale point cloud data that does not require annotated 3D training data or paired RGB images. The proposed approach projects 3D point clouds onto 2D images using virtual cameras and performs semantic segmentation via a foundation 2D model guided by natural language prompts. 3D segmentation is achieved by aggregating predictions from multiple viewpoints through weighted voting. Our method outperforms existing training-free approaches and achieves segmentation accuracy comparable to supervised methods. Moreover, it supports open-vocabulary recognition, enabling users to detect objects using arbitrary text queries, thus overcoming the limitations of traditional supervised approaches.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 29 of its 33 references that are in the map. First posted on arXiv 5 Jan 2026.

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29 of 33 references.

References · 29

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2023Segment Anythingcited by 8,158
  3. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  4. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  5. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  6. 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,274
  7. 2018Dynamic Graph CNN for Learning on Point Cloudscited by 2,220
  8. 2020Point Transformercited by 1,462
  9. 2019KPConv: Flexible and Deformable Convolution for Point Cloudscited by 1,202
  10. 2024Grounded SAM: Assembling Open-World Models for Diverse Visual Taskscited by 914
  11. 2022Language-driven Semantic Segmentationcited by 711
  12. 2019RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Cloudscited by 584
17 more
  1. 2023Point Transformer V3: Simpler, Faster, Strongercited by 579
  2. 2015Multi-view Convolutional Neural Networks for 3D Shape Recognitioncited by 564
  3. 2022OpenScene: 3D Scene Understanding with Open Vocabulariescited by 556
  4. 2021Scaling Open-Vocabulary Image Segmentation with Image-Level Labelscited by 471
  5. 2021PointCLIP: Point Cloud Understanding by CLIPcited by 461
  6. 2022Point Transformer V2: Grouped Vector Attention and Partition-based Poolingcited by 384
  7. 2023OpenMask3D: Open-Vocabulary 3D Instance Segmentationcited by 288
  8. 2022PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learningcited by 186
  9. 2023CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIPcited by 178
  10. 2017Semantic3D.net: A new Large-scale Point Cloud Classification Benchmarkcited by 158
  11. 2023Open3DIS: Open-Vocabulary 3D Instance Segmentation with 2D Mask Guidancecited by 123
  12. 2023RegionPLC: Regional Point-Language Contrastive Learning for Open-World 3D Scene Understandingcited by 93
  13. 2023OpenIns3D: Snap and Lookup for 3D Open-vocabulary Instance Segmentationcited by 82
  14. 2023Open-Vocabulary Point-Cloud Object Detection without 3D Annotationcited by 81
  15. 2022SensatUrban: Learning Semantics from Urban-Scale Photogrammetric Point Cloudscited by 49
  16. 2023Open-vocabulary Panoptic Segmentation with Embedding Modulationcited by 39
  17. 2024OV-Uni3DETR: Towards Unified Open-Vocabulary 3D Object Detection via Cycle-Modality Propagationcited by 19

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  1. 2025All in One: Visual-Description-Guided Unified Point Cloud Segmentation
  2. 2023Geometrically-driven Aggregation for Zero-shot 3D Point Cloud Understanding
  3. 2025Point-MoE: Large-Scale Multi-Dataset Training with Mixture-of-Experts for 3D Semantic Segmentation
  4. 2026Training-Free Open-Vocabulary 3D Point-Cloud Segmentation on the Generalized Few-Shot Benchmark
  5. 2023CLIP2: Contrastive Language-Image-Point Pretraining from Real-World Point Cloud Data
  6. 2026Lang3DSeg: Annotation-Free Open-Vocabulary 3D Segmentation with Point Transformers
  7. 2023Weakly-Supervised 3D Visual Grounding based on Visual Language Alignment
  8. 2025Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language Model