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Models/SOM

SOM

Reported on 6 benchmarks across 4 tasks · 2 papers · 1 SOTA

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

Methodology3 results

Anomaly DetectiononVehicle Claims
AUC· 2022-10-25
65.43
best: 98.65 (Random Forest)
Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings arXiv:2210.14056
3DonNYU-Depth V2
RMSE· 2019-09-10
0.604
best: 0.013 (Defocus/DepthNet (Normalized))
Structure-Attentioned Memory Network for Monocular Depth Estimation arXiv:1909.04594
3DonKITTI Eigen split
absolute relative error· 2019-09-10
0.097
best: 0.029 (SPIDepth)
Structure-Attentioned Memory Network for Monocular Depth Estimation arXiv:1909.04594

Computer Vision2 results

Depth EstimationonNYU-Depth V2
RMSE· 2019-09-10
0.604
best: 0.013 (Defocus/DepthNet (Normalized))
Structure-Attentioned Memory Network for Monocular Depth Estimation arXiv:1909.04594
Depth EstimationonKITTI Eigen split
absolute relative error· 2019-09-10
0.097
best: 0.029 (SPIDepth)
Structure-Attentioned Memory Network for Monocular Depth Estimation arXiv:1909.04594

Graphs1 result

Unsupervised Anomaly DetectiononVehicle Claims
AUC· 2022-10-25
65.43
SOTA
Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings arXiv:2210.14056