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/DistDepth

DistDepth

Reported on 18 benchmarks across 2 tasks · 1 paper · 18 SOTA

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

Computer Vision9 results

  • Depth EstimationonVA (Virtual Apartment)
    Absolute relative error (AbsRel)· 2021-12-04
    0.175
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • Depth EstimationonVA (Virtual Apartment)
    Log root mean square error (RMSE_log)· 2021-12-04
    0.213
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • Depth EstimationonVA (Virtual Apartment)
    Mean average error (MAE) · 2021-12-04
    0.253
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • Depth EstimationonVA (Virtual Apartment)
    Root mean square error (RMSE)· 2021-12-04
    0.374
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • Depth EstimationonNYU-Depth V2 self-supervised
    Absolute relative error (AbsRel)· 2021-12-04
    0.13
    best: 0.126 (IndoorDepth)
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • Depth EstimationonNYU-Depth V2 self-supervised
    Root mean square error (RMSE)· 2021-12-04
    0.517
    best: 0.494 (IndoorDepth)
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • Depth EstimationonNYU-Depth V2 self-supervised
    delta_1· 2021-12-04
    83.2
    best: 84.5 (IndoorDepth)
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • Depth EstimationonNYU-Depth V2 self-supervised
    delta_2· 2021-12-04
    96.3
    best: 96.5 (IndoorDepth)
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • Depth EstimationonNYU-Depth V2 self-supervised
    delta_3· 2021-12-04
    99
    best: 99.1 (IndoorDepth)
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306

Methodology9 results

  • 3DonVA (Virtual Apartment)
    Absolute relative error (AbsRel)· 2021-12-04
    0.175
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • 3DonVA (Virtual Apartment)
    Log root mean square error (RMSE_log)· 2021-12-04
    0.213
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • 3DonVA (Virtual Apartment)
    Mean average error (MAE) · 2021-12-04
    0.253
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • 3DonVA (Virtual Apartment)
    Root mean square error (RMSE)· 2021-12-04
    0.374
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • 3DonNYU-Depth V2 self-supervised
    Absolute relative error (AbsRel)· 2021-12-04
    0.13
    best: 0.126 (IndoorDepth)
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • 3DonNYU-Depth V2 self-supervised
    Root mean square error (RMSE)· 2021-12-04
    0.517
    best: 0.494 (IndoorDepth)
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • 3DonNYU-Depth V2 self-supervised
    delta_1· 2021-12-04
    83.2
    best: 84.5 (IndoorDepth)
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • 3DonNYU-Depth V2 self-supervised
    delta_2· 2021-12-04
    96.3
    best: 96.5 (IndoorDepth)
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306
  • 3DonNYU-Depth V2 self-supervised
    delta_3· 2021-12-04
    99
    best: 99.1 (IndoorDepth)
    SOTA
    Toward Practical Monocular Indoor Depth EstimationarXiv:2112.02306