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SotA/Computer Vision/Surface Normals Estimation/NYU Depth v2

Surface Normals Estimation on NYU Depth v2

Metric: % < 30 (higher is better)

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#Model↕% < 30▼Extra DataPaperDate↕Code
1Metric3Dv2(L, FT)89.8YesMetric3Dv2: A Versatile Monocular Geometric Foun...2024-03-22Code
2PolyMaX(ConvNeXt-L)87.83NoPolyMaX: General Dense Prediction with Mask Tran...2023-11-09Code
3iDisc85.6NoiDisc: Internal Discretization for Monocular Dep...2023-04-13Code
4Bae et al.85.2NoEstimating and Exploiting the Aleatoric Uncertai...2021-09-20Code
5Floors are Flat77.3NoFloors are Flat: Leveraging Semantics for Real-T...2019-06-16Code