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Models/2D-MobileStereoNet

2D-MobileStereoNet

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

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

Computer Vision6 results

  • Depth Estimationonsceneflow
    EPE· 2021-08-22
    1.14
    SOTA
    MobileStereoNet: Towards Lightweight Deep Networks for Stereo MatchingarXiv:2108.09770
  • Stereo Depth Estimationonsceneflow
    EPE· 2021-08-22
    1.14
    SOTA
    MobileStereoNet: Towards Lightweight Deep Networks for Stereo MatchingarXiv:2108.09770
  • Depth Estimationonsceneflow
    Average End-Point Error· 2021-08-22
    1.14
    best: 0.8 (3D-MobileStereoNet)
    MobileStereoNet: Towards Lightweight Deep Networks for Stereo MatchingarXiv:2108.09770
  • Depth EstimationonKITTI2015
    three pixel error· 2021-08-22
    2.67
    best: 1.69 (3D-MobileStereoNet)
    MobileStereoNet: Towards Lightweight Deep Networks for Stereo MatchingarXiv:2108.09770
  • Stereo Depth Estimationonsceneflow
    Average End-Point Error· 2021-08-22
    1.14
    best: 0.8 (3D-MobileStereoNet)
    MobileStereoNet: Towards Lightweight Deep Networks for Stereo MatchingarXiv:2108.09770
  • Stereo Depth EstimationonKITTI2015
    three pixel error· 2021-08-22
    2.67
    best: 1.69 (3D-MobileStereoNet)
    MobileStereoNet: Towards Lightweight Deep Networks for Stereo MatchingarXiv:2108.09770

Methodology3 results

  • 3Donsceneflow
    EPE· 2021-08-22
    1.14
    SOTA
    MobileStereoNet: Towards Lightweight Deep Networks for Stereo MatchingarXiv:2108.09770
  • 3Donsceneflow
    Average End-Point Error· 2021-08-22
    1.14
    best: 0.8 (3D-MobileStereoNet)
    MobileStereoNet: Towards Lightweight Deep Networks for Stereo MatchingarXiv:2108.09770
  • 3DonKITTI2015
    three pixel error· 2021-08-22
    2.67
    best: 1.69 (3D-MobileStereoNet)
    MobileStereoNet: Towards Lightweight Deep Networks for Stereo MatchingarXiv:2108.09770