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Models/BUCTD-preNet-W48 (CID-W32)

BUCTD-preNet-W48 (CID-W32)

Reported on 8 benchmarks across 4 tasks · 1 paper · 4 SOTA

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

Computer Vision4 results

  • Pose EstimationonMarmoset-8K
    mAP· 2023-06-13
    93.3
    SOTA
    Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguityarXiv:2306.07879
  • Animal Pose EstimationonMarmoset-8K
    mAP· 2023-06-13
    93.3
    SOTA
    Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguityarXiv:2306.07879
  • Pose EstimationonFish-100
    mAP· 2023-06-13
    88
    best: 89.1 (HRNet-W48 + Faster R-CNN)
    Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguityarXiv:2306.07879
  • Animal Pose EstimationonFish-100
    mAP· 2023-06-13
    88
    best: 89.1 (HRNet-W48 + Faster R-CNN)
    Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguityarXiv:2306.07879

Methodology2 results

  • 3DonMarmoset-8K
    mAP· 2023-06-13
    93.3
    SOTA
    Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguityarXiv:2306.07879
  • 3DonFish-100
    mAP· 2023-06-13
    88
    best: 89.1 (HRNet-W48 + Faster R-CNN)
    Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguityarXiv:2306.07879

Audio2 results

  • 1 Image, 2*2 StitchionMarmoset-8K
    mAP· 2023-06-13
    93.3
    SOTA
    Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguityarXiv:2306.07879
  • 1 Image, 2*2 StitchionFish-100
    mAP· 2023-06-13
    88
    best: 89.1 (HRNet-W48 + Faster R-CNN)
    Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguityarXiv:2306.07879