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Models/DepthMaster

DepthMaster

Reported on 12 benchmarks across 2 tasks · 1 paper · 2 SOTA

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

Computer Vision6 results

  • Depth EstimationonETH3D
    Delta < 1.25· 2025-01-05
    0.974
    best: 0.981 (Distill Any Depth)
    SOTA
    DepthMaster: Taming Diffusion Models for Monocular Depth EstimationarXiv:2501.02576
  • Depth EstimationonNYU-Depth V2
    Delta < 1.25· uses extra data· 2025-01-05
    0.972
    best: 0.989 (UniK3D (FT, metric))
    DepthMaster: Taming Diffusion Models for Monocular Depth EstimationarXiv:2501.02576
  • Depth EstimationonNYU-Depth V2
    absolute relative error· uses extra data· 2025-01-05
    0.05
    best: 0.026 (HybridDepth)
    DepthMaster: Taming Diffusion Models for Monocular Depth EstimationarXiv:2501.02576
  • Depth EstimationonETH3D
    absolute relative error· 2025-01-05
    0.053
    best: 0.0121 (HDN)
    DepthMaster: Taming Diffusion Models for Monocular Depth EstimationarXiv:2501.02576
  • Depth EstimationonKITTI Eigen split
    Delta < 1.25· uses extra data· 2025-01-05
    0.937
    best: 0.99 (SPIDepth)
    DepthMaster: Taming Diffusion Models for Monocular Depth EstimationarXiv:2501.02576
  • Depth EstimationonKITTI Eigen split
    absolute relative error· uses extra data· 2025-01-05
    0.082
    best: 0.029 (SPIDepth)
    DepthMaster: Taming Diffusion Models for Monocular Depth EstimationarXiv:2501.02576

Methodology6 results

  • 3DonETH3D
    Delta < 1.25· 2025-01-05
    0.974
    best: 0.981 (Distill Any Depth)
    SOTA
    DepthMaster: Taming Diffusion Models for Monocular Depth EstimationarXiv:2501.02576
  • 3DonNYU-Depth V2
    Delta < 1.25· uses extra data· 2025-01-05
    0.972
    best: 0.989 (UniK3D (FT, metric))
    DepthMaster: Taming Diffusion Models for Monocular Depth EstimationarXiv:2501.02576
  • 3DonNYU-Depth V2
    absolute relative error· uses extra data· 2025-01-05
    0.05
    best: 0.026 (HybridDepth)
    DepthMaster: Taming Diffusion Models for Monocular Depth EstimationarXiv:2501.02576
  • 3DonETH3D
    absolute relative error· 2025-01-05
    0.053
    best: 0.0121 (HDN)
    DepthMaster: Taming Diffusion Models for Monocular Depth EstimationarXiv:2501.02576
  • 3DonKITTI Eigen split
    Delta < 1.25· uses extra data· 2025-01-05
    0.937
    best: 0.99 (SPIDepth)
    DepthMaster: Taming Diffusion Models for Monocular Depth EstimationarXiv:2501.02576
  • 3DonKITTI Eigen split
    absolute relative error· uses extra data· 2025-01-05
    0.082
    best: 0.029 (SPIDepth)
    DepthMaster: Taming Diffusion Models for Monocular Depth EstimationarXiv:2501.02576