Tasks SotA Datasets Papers Methods Submit About

Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable Benchmarks All SotA Datasets Papers Methods

Community

Submit Results About

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/HGs + SA + Norm + GHCU

HGs + SA + Norm + GHCU

Reported on 15 benchmarks across 5 tasks · 1 paper

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

Computer Vision6 results

Face Reconstructionon300W
NME_inter-pupil (%, Challenge)· 2019-03-26
6.38
best: 10.59 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661
Face Reconstructionon300W
NME_inter-pupil (%, Common)· 2019-03-26
3.45
best: 6.15 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661
Face Reconstructionon300W
NME_inter-pupil (%, Full)· 2019-03-26
4.02
best: 7.01 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661
3D Face Reconstructionon300W
NME_inter-pupil (%, Challenge)· 2019-03-26
6.38
best: 10.59 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661
3D Face Reconstructionon300W
NME_inter-pupil (%, Common)· 2019-03-26
3.45
best: 6.15 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661
3D Face Reconstructionon300W
NME_inter-pupil (%, Full)· 2019-03-26
4.02
best: 7.01 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661

Music3 results

Facial Recognition and Modellingon300W
NME_inter-pupil (%, Challenge)· 2019-03-26
6.38
best: 10.59 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661
Facial Recognition and Modellingon300W
NME_inter-pupil (%, Common)· 2019-03-26
3.45
best: 6.15 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661
Facial Recognition and Modellingon300W
NME_inter-pupil (%, Full)· 2019-03-26
4.02
best: 7.01 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661

Methodology3 results

3Don300W
NME_inter-pupil (%, Challenge)· 2019-03-26
6.38
best: 10.59 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661
3Don300W
NME_inter-pupil (%, Common)· 2019-03-26
3.45
best: 6.15 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661
3Don300W
NME_inter-pupil (%, Full)· 2019-03-26
4.02
best: 7.01 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661

Medical3 results

3D Face Modellingon300W
NME_inter-pupil (%, Challenge)· 2019-03-26
6.38
best: 10.59 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661
3D Face Modellingon300W
NME_inter-pupil (%, Common)· 2019-03-26
3.45
best: 6.15 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661
3D Face Modellingon300W
NME_inter-pupil (%, Full)· 2019-03-26
4.02
best: 7.01 (3DDFA)
Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection arXiv:1903.10661