Unsupervised 3D Semantic Segmentation
1개 벤치마크 · 논문 3편 · 이 태스크의 논문 보기 →
Benchmarks
ScanNetV2
결과 6개
Most implemented
LogoSP: Local-global Grouping of Superpoints for Unsupervised Semantic Segmentation of 3D Point Clouds
2025-06-09 · 구현 1개
Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color Contrast
2023-05-31 · 구현 1개
SL3D: Self-supervised-Self-labeled 3D Recognition
2022-10-30 · 구현 1개
Papers
LogoSP: Local-global Grouping of Superpoints for Unsupervised Semantic Segmentation of 3D Point Clouds
2025-06-09 · CVPR 2025 1
· Zihui Zhang, Weisheng Dai, Hongtao Wen, Bo Yang
We study the problem of unsupervised 3D semantic segmentation on raw point clouds without needing human labels in training. Existing methods usually formulate this problem into learning per-point local features followed …
3D Semantic SegmentationSegmentationSemantic SegmentationUnsupervised 3D Semantic Segmentation+1Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color Contrast
2023-05-31
· Guofan Fan, Zekun Qi, Wenkai Shi, Kaisheng Ma
Geometry and color information provided by the point clouds are both crucial for 3D scene understanding. Two pieces of information characterize the different aspects of point clouds, but existing methods lack an elaborat…
3D Instance Segmentation3D Object Detection3D Semantic SegmentationDeep Clustering+6SL3D: Self-supervised-Self-labeled 3D Recognition
2022-10-30
· Fernando Julio Cendra, Lan Ma, Jiajun Shen, Xiaojuan Qi
Deep learning has attained remarkable success in many 3D visual recognition tasks, including shape classification, object detection, and semantic segmentation. However, many of these results rely on manually collecting d…
ClusteringObjectobject-detectionObject Detection+3