TasksSotADatasetsPapersMethodsSubmitAbout
Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable BenchmarksAll SotADatasetsPapersMethods

Community

Submit ResultsAbout

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/Point-GCC+TR3D

Point-GCC+TR3D

Reported on 36 benchmarks across 6 tasks · 1 paper · 12 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology24 results

  • 3DonS3DIS
    mAP@0.25· uses extra data· 2023-05-31
    75.1
    best: 75.2 (UniDet3D)
    SOTA
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 3DonS3DIS
    mAP@0.5· uses extra data· 2023-05-31
    56.7
    best: 60.8 (UniDet3D)
    SOTA
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 2D ClassificationonS3DIS
    mAP@0.25· uses extra data· 2023-05-31
    75.1
    best: 75.2 (UniDet3D)
    SOTA
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 2D ClassificationonS3DIS
    mAP@0.5· uses extra data· 2023-05-31
    56.7
    best: 60.8 (UniDet3D)
    SOTA
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 2D Object DetectiononS3DIS
    mAP@0.25· uses extra data· 2023-05-31
    75.1
    best: 75.2 (UniDet3D)
    SOTA
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 2D Object DetectiononS3DIS
    mAP@0.5· uses extra data· 2023-05-31
    56.7
    best: 60.8 (UniDet3D)
    SOTA
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 16konS3DIS
    mAP@0.25· uses extra data· 2023-05-31
    75.1
    best: 75.2 (UniDet3D)
    SOTA
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 16konS3DIS
    mAP@0.5· uses extra data· 2023-05-31
    56.7
    best: 60.8 (UniDet3D)
    SOTA
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 3DonSUN-RGBD val
    mAP@0.25· 2023-05-31
    67.7
    best: 69.7 (Point-GCC+TR3D+FF)
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 3DonSUN-RGBD val
    mAP@0.5· 2023-05-31
    51
    best: 54 (Point-GCC+TR3D+FF)
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 3DonScanNetV2
    mAP@0.25· 2023-05-31
    73.1
    best: 78.8 (DEST (based on V-DETR) (TTA))
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 3DonScanNetV2
    mAP@0.5· 2023-05-31
    59.6
    best: 67.9 (DEST (based on V-DETR) (TTA))
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 2D ClassificationonSUN-RGBD val
    mAP@0.25· 2023-05-31
    67.7
    best: 69.7 (Point-GCC+TR3D+FF)
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 2D ClassificationonSUN-RGBD val
    mAP@0.5· 2023-05-31
    51
    best: 54 (Point-GCC+TR3D+FF)
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 2D ClassificationonScanNetV2
    mAP@0.25· 2023-05-31
    73.1
    best: 78.8 (DEST (based on V-DETR) (TTA))
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 2D ClassificationonScanNetV2
    mAP@0.5· 2023-05-31
    59.6
    best: 67.9 (DEST (based on V-DETR) (TTA))
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 2D Object DetectiononSUN-RGBD val
    mAP@0.25· 2023-05-31
    67.7
    best: 69.7 (Point-GCC+TR3D+FF)
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 2D Object DetectiononSUN-RGBD val
    mAP@0.5· 2023-05-31
    51
    best: 54 (Point-GCC+TR3D+FF)
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 2D Object DetectiononScanNetV2
    mAP@0.25· 2023-05-31
    73.1
    best: 78.8 (DEST (based on V-DETR) (TTA))
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 2D Object DetectiononScanNetV2
    mAP@0.5· 2023-05-31
    59.6
    best: 67.9 (DEST (based on V-DETR) (TTA))
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 16konSUN-RGBD val
    mAP@0.25· 2023-05-31
    67.7
    best: 69.7 (Point-GCC+TR3D+FF)
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 16konSUN-RGBD val
    mAP@0.5· 2023-05-31
    51
    best: 54 (Point-GCC+TR3D+FF)
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 16konScanNetV2
    mAP@0.25· 2023-05-31
    73.1
    best: 78.8 (DEST (based on V-DETR) (TTA))
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 16konScanNetV2
    mAP@0.5· 2023-05-31
    59.6
    best: 67.9 (DEST (based on V-DETR) (TTA))
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623

Computer Vision12 results

  • Object DetectiononS3DIS
    mAP@0.25· uses extra data· 2023-05-31
    75.1
    best: 75.2 (UniDet3D)
    SOTA
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • Object DetectiononS3DIS
    mAP@0.5· uses extra data· 2023-05-31
    56.7
    best: 60.8 (UniDet3D)
    SOTA
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 3D Object DetectiononS3DIS
    mAP@0.25· uses extra data· 2023-05-31
    75.1
    best: 75.2 (UniDet3D)
    SOTA
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 3D Object DetectiononS3DIS
    mAP@0.5· uses extra data· 2023-05-31
    56.7
    best: 60.8 (UniDet3D)
    SOTA
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • Object DetectiononSUN-RGBD val
    mAP@0.25· 2023-05-31
    67.7
    best: 69.7 (Point-GCC+TR3D+FF)
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • Object DetectiononSUN-RGBD val
    mAP@0.5· 2023-05-31
    51
    best: 54 (Point-GCC+TR3D+FF)
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • Object DetectiononScanNetV2
    mAP@0.25· 2023-05-31
    73.1
    best: 78.8 (DEST (based on V-DETR) (TTA))
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • Object DetectiononScanNetV2
    mAP@0.5· 2023-05-31
    59.6
    best: 67.9 (DEST (based on V-DETR) (TTA))
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 3D Object DetectiononSUN-RGBD val
    mAP@0.25· 2023-05-31
    67.7
    best: 69.7 (Point-GCC+TR3D+FF)
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 3D Object DetectiononSUN-RGBD val
    mAP@0.5· 2023-05-31
    51
    best: 54 (Point-GCC+TR3D+FF)
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 3D Object DetectiononScanNetV2
    mAP@0.25· 2023-05-31
    73.1
    best: 78.8 (DEST (based on V-DETR) (TTA))
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623
  • 3D Object DetectiononScanNetV2
    mAP@0.5· 2023-05-31
    59.6
    best: 67.9 (DEST (based on V-DETR) (TTA))
    Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastarXiv:2305.19623