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Models/RLE (256x192)

RLE (256x192)

Reported on 9 benchmarks across 3 tasks · 1 paper · 6 SOTA

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

Computer Vision3 results

  • Pose EstimationonCOCO val2017
    AP50· 2021-07-23
    88.9
    best: 93.7 (CCNet (ViTPose-B_GT-bbox_256x192))
    SOTA
    Human Pose Regression with Residual Log-likelihood EstimationarXiv:2107.11291
  • Pose EstimationonCOCO val2017
    AP75· 2021-07-23
    78.3
    best: 85 (CCNet (ViTPose-B_GT-bbox_256x192))
    SOTA
    Human Pose Regression with Residual Log-likelihood EstimationarXiv:2107.11291
  • Pose EstimationonCOCO val2017
    AP· 2021-07-23
    71.3
    best: 78.1 (CCNet (ViTPose-B_GT-bbox_256x192))
    Human Pose Regression with Residual Log-likelihood EstimationarXiv:2107.11291

Methodology3 results

  • 3DonCOCO val2017
    AP50· 2021-07-23
    88.9
    best: 93.7 (CCNet (ViTPose-B_GT-bbox_256x192))
    SOTA
    Human Pose Regression with Residual Log-likelihood EstimationarXiv:2107.11291
  • 3DonCOCO val2017
    AP75· 2021-07-23
    78.3
    best: 85 (CCNet (ViTPose-B_GT-bbox_256x192))
    SOTA
    Human Pose Regression with Residual Log-likelihood EstimationarXiv:2107.11291
  • 3DonCOCO val2017
    AP· 2021-07-23
    71.3
    best: 78.1 (CCNet (ViTPose-B_GT-bbox_256x192))
    Human Pose Regression with Residual Log-likelihood EstimationarXiv:2107.11291

Audio3 results

  • 1 Image, 2*2 StitchionCOCO val2017
    AP50· 2021-07-23
    88.9
    best: 93.7 (CCNet (ViTPose-B_GT-bbox_256x192))
    SOTA
    Human Pose Regression with Residual Log-likelihood EstimationarXiv:2107.11291
  • 1 Image, 2*2 StitchionCOCO val2017
    AP75· 2021-07-23
    78.3
    best: 85 (CCNet (ViTPose-B_GT-bbox_256x192))
    SOTA
    Human Pose Regression with Residual Log-likelihood EstimationarXiv:2107.11291
  • 1 Image, 2*2 StitchionCOCO val2017
    AP· 2021-07-23
    71.3
    best: 78.1 (CCNet (ViTPose-B_GT-bbox_256x192))
    Human Pose Regression with Residual Log-likelihood EstimationarXiv:2107.11291