Prodpoly

Reported on 19 benchmarks across 7 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 Vision7 results

Face ReconstructiononAgeDB-30
Accuracy· 2020-06-20
0.98467
best: 71.62 (USynthFace)
SOTA
Deep Polynomial Neural Networks arXiv:2006.13026
Face ReconstructiononLFW
Accuracy· uses extra data· 2020-06-20
0.99833
best: 0.998667 (GhostFaceNetV2-1 (MS1MV3))
SOTA
Deep Polynomial Neural Networks arXiv:2006.13026
Face ReconstructiononCALFW
Accuracy· 2020-06-20
0.96233
best: 96.15 (DiscFace)
SOTA
Deep Polynomial Neural Networks arXiv:2006.13026
3D Face ReconstructiononAgeDB-30
Accuracy· 2020-06-20
0.98467
best: 71.62 (USynthFace)
SOTA
Deep Polynomial Neural Networks arXiv:2006.13026
3D Face ReconstructiononLFW
Accuracy· uses extra data· 2020-06-20
0.99833
best: 0.998667 (GhostFaceNetV2-1 (MS1MV3))
SOTA
Deep Polynomial Neural Networks arXiv:2006.13026
3D Face ReconstructiononCALFW
Accuracy· 2020-06-20
0.96233
best: 96.15 (DiscFace)
SOTA
Deep Polynomial Neural Networks arXiv:2006.13026
Image ClassificationonCIFAR-10
Percentage correct· 2020-06-20
94.9
best: 99.5 (ViT-H/14)
Deep Polynomial Neural Networks arXiv:2006.13026

Face RecognitiononAgeDB-30
Accuracy· 2020-06-20
0.98467
best: 71.62 (USynthFace)
SOTA
Deep Polynomial Neural Networks arXiv:2006.13026
Face RecognitiononLFW
Accuracy· uses extra data· 2020-06-20
0.99833
best: 0.998667 (GhostFaceNetV2-1 (MS1MV3))
SOTA
Deep Polynomial Neural Networks arXiv:2006.13026
Face RecognitiononCALFW
Accuracy· 2020-06-20
0.96233
SOTA
Deep Polynomial Neural Networks arXiv:2006.13026
3DonAgeDB-30
Accuracy· 2020-06-20
0.98467
best: 71.62 (USynthFace)
SOTA
Deep Polynomial Neural Networks arXiv:2006.13026
3DonLFW
Accuracy· uses extra data· 2020-06-20
0.99833
best: 0.998667 (GhostFaceNetV2-1 (MS1MV3))
SOTA
Deep Polynomial Neural Networks arXiv:2006.13026
3DonCALFW
Accuracy· 2020-06-20
0.96233
best: 96.15 (DiscFace)
SOTA
Deep Polynomial Neural Networks arXiv:2006.13026