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.

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

Surface Normals Estimation on NYU Depth v2

Metric: % < 22.5 (higher is better)

LeaderboardDataset
Loading chart...

Results

Submit a result
#Model↕% < 22.5▼Extra DataPaperDate↕Code
1Metric3Dv2(L, FT)84.9YesMetric3Dv2: A Versatile Monocular Geometric Foun...2024-03-22Code
2PolyMaX(ConvNeXt-L)82.28NoPolyMaX: General Dense Prediction with Mask Tran...2023-11-09Code
3iDisc79.8NoiDisc: Internal Discretization for Monocular Dep...2023-04-13Code
4Bae et al.79.3NoEstimating and Exploiting the Aleatoric Uncertai...2021-09-20Code
5Floors are Flat72.2NoFloors are Flat: Leveraging Semantics for Real-T...2019-06-16Code