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/ReCon+PPT

ReCon+PPT

Reported on 9 benchmarks across 3 tasks · 1 paper

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

Computer Vision9 results

  • Shape Representation Of 3D Point CloudsonScanObjectNN
    OBJ-BG (OA)· 2024-08-21
    95.01
    best: 99.48 (PointGST)
    Positional Prompt Tuning for Efficient 3D Representation LearningarXiv:2408.11567
  • Shape Representation Of 3D Point CloudsonScanObjectNN
    OBJ-ONLY (OA)· 2024-08-21
    93.28
    best: 97.76 (PointGST)
    Positional Prompt Tuning for Efficient 3D Representation LearningarXiv:2408.11567
  • Shape Representation Of 3D Point CloudsonScanObjectNN
    Overall Accuracy· 2024-08-21
    89.52
    best: 97.2 (OmniVec2)
    Positional Prompt Tuning for Efficient 3D Representation LearningarXiv:2408.11567
  • 3D Point Cloud ClassificationonScanObjectNN
    OBJ-BG (OA)· 2024-08-21
    95.01
    best: 99.48 (PointGST)
    Positional Prompt Tuning for Efficient 3D Representation LearningarXiv:2408.11567
  • 3D Point Cloud ClassificationonScanObjectNN
    OBJ-ONLY (OA)· 2024-08-21
    93.28
    best: 97.76 (PointGST)
    Positional Prompt Tuning for Efficient 3D Representation LearningarXiv:2408.11567
  • 3D Point Cloud ClassificationonScanObjectNN
    Overall Accuracy· 2024-08-21
    89.52
    best: 97.2 (OmniVec2)
    Positional Prompt Tuning for Efficient 3D Representation LearningarXiv:2408.11567
  • 3D Point Cloud ReconstructiononScanObjectNN
    OBJ-BG (OA)· 2024-08-21
    95.01
    best: 99.48 (PointGST)
    Positional Prompt Tuning for Efficient 3D Representation LearningarXiv:2408.11567
  • 3D Point Cloud ReconstructiononScanObjectNN
    OBJ-ONLY (OA)· 2024-08-21
    93.28
    best: 97.76 (PointGST)
    Positional Prompt Tuning for Efficient 3D Representation LearningarXiv:2408.11567
  • 3D Point Cloud ReconstructiononScanObjectNN
    Overall Accuracy· 2024-08-21
    89.52
    best: 97.2 (OmniVec2)
    Positional Prompt Tuning for Efficient 3D Representation LearningarXiv:2408.11567