{"task":"3D Face Reconstruction","dataset":"AFLW2000-3D","metric_names":["Mean NME ","Mean NME"],"rows":[{"id":3768,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"SADRNet","metrics":{"Mean NME ":"3.25%"},"paper_url":"https://arxiv.org/abs/2106.03021v1","paper_title":"SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction","paper_date":"2021-06-06","code_links":[{"title":"MCG-NJU/SADRNet","url":"https://github.com/MCG-NJU/SADRNet"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":3769,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"VGG-F","metrics":{"Mean NME ":"3.42%"},"paper_url":"https://arxiv.org/abs/2103.16554v2","paper_title":"Pre-training strategies and datasets for facial representation learning","paper_date":"2021-03-30","code_links":[{"title":"tomas-gajarsky/facetorch","url":"https://github.com/tomas-gajarsky/facetorch"},{"title":"1adrianb/unsupervised-face-representation","url":"https://github.com/1adrianb/unsupervised-face-representation"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":3770,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"B-spline FFD","metrics":{"Mean NME ":"3.51%"},"paper_url":"https://arxiv.org/abs/2105.14857v2","paper_title":"Learning Free-Form Deformation for 3D Face Reconstruction from In-The-Wild Images","paper_date":"2021-05-31","code_links":[],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":3771,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"3DDFA-V2","metrics":{"Mean NME ":"3.56%"},"paper_url":"https://arxiv.org/abs/2009.09960v2","paper_title":"Towards Fast, Accurate and Stable 3D Dense Face Alignment","paper_date":"2020-09-21","code_links":[{"title":"cleardusk/3DDFA","url":"https://github.com/cleardusk/3DDFA"},{"title":"cleardusk/3DDFA_V2","url":"https://github.com/cleardusk/3DDFA_V2"},{"title":"scoutant/face-blur","url":"https://github.com/scoutant/face-blur"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":3772,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"PRN","metrics":{"Mean NME ":"3.9625%"},"paper_url":"http://arxiv.org/abs/1803.07835v1","paper_title":"Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network","paper_date":"2018-03-21","code_links":[{"title":"YadiraF/PRNet","url":"https://github.com/YadiraF/PRNet"},{"title":"jimmy0087/faceai-master","url":"https://github.com/jimmy0087/faceai-master"},{"title":"minoring/PRNet","url":"https://github.com/minoring/PRNet"},{"title":"heathentw/prnet-tf2","url":"https://github.com/heathentw/prnet-tf2"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":3773,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"3DDFA","metrics":{"Mean NME ":"5.3695%"},"paper_url":"http://arxiv.org/abs/1511.07212v1","paper_title":"Face Alignment Across Large Poses: A 3D Solution","paper_date":"2015-11-23","code_links":[],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":3774,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"DeFA","metrics":{"Mean NME ":"5.6454%"},"paper_url":"http://arxiv.org/abs/1709.01442v1","paper_title":"Dense Face Alignment","paper_date":"2017-09-05","code_links":[{"title":"yaojieliu/ICCVW2017-DenseFaceAlignment","url":"https://github.com/yaojieliu/ICCVW2017-DenseFaceAlignment"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":3775,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"DSFNet-is","metrics":{"Mean NME":"3.16"},"paper_url":"https://arxiv.org/abs/2305.11522v1","paper_title":"DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment","paper_date":"2023-05-19","code_links":[{"title":"lhyfst/dsfnet","url":"https://github.com/lhyfst/dsfnet"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":73707,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"SADRNet","metrics":{"Mean NME ":"3.25%"},"paper_url":"https://arxiv.org/abs/2106.03021v1","paper_title":"SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction","paper_date":"2021-06-06","code_links":[{"title":"MCG-NJU/SADRNet","url":"https://github.com/MCG-NJU/SADRNet"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":73708,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"VGG-F","metrics":{"Mean NME ":"3.42%"},"paper_url":"https://arxiv.org/abs/2103.16554v2","paper_title":"Pre-training strategies and datasets for facial representation learning","paper_date":"2021-03-30","code_links":[{"title":"tomas-gajarsky/facetorch","url":"https://github.com/tomas-gajarsky/facetorch"},{"title":"1adrianb/unsupervised-face-representation","url":"https://github.com/1adrianb/unsupervised-face-representation"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":73709,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"B-spline FFD","metrics":{"Mean NME ":"3.51%"},"paper_url":"https://arxiv.org/abs/2105.14857v2","paper_title":"Learning Free-Form Deformation for 3D Face Reconstruction from In-The-Wild Images","paper_date":"2021-05-31","code_links":[],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":73710,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"3DDFA-V2","metrics":{"Mean NME ":"3.56%"},"paper_url":"https://arxiv.org/abs/2009.09960v2","paper_title":"Towards Fast, Accurate and Stable 3D Dense Face Alignment","paper_date":"2020-09-21","code_links":[{"title":"cleardusk/3DDFA","url":"https://github.com/cleardusk/3DDFA"},{"title":"cleardusk/3DDFA_V2","url":"https://github.com/cleardusk/3DDFA_V2"},{"title":"scoutant/face-blur","url":"https://github.com/scoutant/face-blur"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":73711,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"PRN","metrics":{"Mean NME ":"3.9625%"},"paper_url":"http://arxiv.org/abs/1803.07835v1","paper_title":"Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network","paper_date":"2018-03-21","code_links":[{"title":"YadiraF/PRNet","url":"https://github.com/YadiraF/PRNet"},{"title":"jimmy0087/faceai-master","url":"https://github.com/jimmy0087/faceai-master"},{"title":"minoring/PRNet","url":"https://github.com/minoring/PRNet"},{"title":"heathentw/prnet-tf2","url":"https://github.com/heathentw/prnet-tf2"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":73712,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"3DDFA","metrics":{"Mean NME ":"5.3695%"},"paper_url":"http://arxiv.org/abs/1511.07212v1","paper_title":"Face Alignment Across Large Poses: A 3D Solution","paper_date":"2015-11-23","code_links":[],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":73713,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"DeFA","metrics":{"Mean NME ":"5.6454%"},"paper_url":"http://arxiv.org/abs/1709.01442v1","paper_title":"Dense Face Alignment","paper_date":"2017-09-05","code_links":[{"title":"yaojieliu/ICCVW2017-DenseFaceAlignment","url":"https://github.com/yaojieliu/ICCVW2017-DenseFaceAlignment"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":73714,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"DSFNet-is","metrics":{"Mean NME":"3.16"},"paper_url":"https://arxiv.org/abs/2305.11522v1","paper_title":"DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment","paper_date":"2023-05-19","code_links":[{"title":"lhyfst/dsfnet","url":"https://github.com/lhyfst/dsfnet"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":81800,"task":"3D Face Reconstruction","parent_task":"3D","dataset":"AFLW2000-3D","model_name":"SADRNet","metrics":{"Mean NME ":"3.25%"},"paper_url":"https://arxiv.org/abs/2106.03021v1","paper_title":"SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction","paper_date":"2021-06-06","code_links":[{"title":"MCG-NJU/SADRNet","url":"https://github.com/MCG-NJU/SADRNet"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":81801,"task":"3D Face Reconstruction","parent_task":"3D","dataset":"AFLW2000-3D","model_name":"VGG-F","metrics":{"Mean NME ":"3.42%"},"paper_url":"https://arxiv.org/abs/2103.16554v2","paper_title":"Pre-training strategies and datasets for facial representation learning","paper_date":"2021-03-30","code_links":[{"title":"tomas-gajarsky/facetorch","url":"https://github.com/tomas-gajarsky/facetorch"},{"title":"1adrianb/unsupervised-face-representation","url":"https://github.com/1adrianb/unsupervised-face-representation"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":81802,"task":"3D Face Reconstruction","parent_task":"3D","dataset":"AFLW2000-3D","model_name":"B-spline FFD","metrics":{"Mean NME ":"3.51%"},"paper_url":"https://arxiv.org/abs/2105.14857v2","paper_title":"Learning Free-Form Deformation for 3D Face Reconstruction from In-The-Wild Images","paper_date":"2021-05-31","code_links":[],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":81803,"task":"3D Face Reconstruction","parent_task":"3D","dataset":"AFLW2000-3D","model_name":"3DDFA-V2","metrics":{"Mean NME ":"3.56%"},"paper_url":"https://arxiv.org/abs/2009.09960v2","paper_title":"Towards Fast, Accurate and Stable 3D Dense Face Alignment","paper_date":"2020-09-21","code_links":[{"title":"cleardusk/3DDFA","url":"https://github.com/cleardusk/3DDFA"},{"title":"cleardusk/3DDFA_V2","url":"https://github.com/cleardusk/3DDFA_V2"},{"title":"scoutant/face-blur","url":"https://github.com/scoutant/face-blur"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":81804,"task":"3D Face Reconstruction","parent_task":"3D","dataset":"AFLW2000-3D","model_name":"PRN","metrics":{"Mean NME ":"3.9625%"},"paper_url":"http://arxiv.org/abs/1803.07835v1","paper_title":"Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network","paper_date":"2018-03-21","code_links":[{"title":"YadiraF/PRNet","url":"https://github.com/YadiraF/PRNet"},{"title":"jimmy0087/faceai-master","url":"https://github.com/jimmy0087/faceai-master"},{"title":"minoring/PRNet","url":"https://github.com/minoring/PRNet"},{"title":"heathentw/prnet-tf2","url":"https://github.com/heathentw/prnet-tf2"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":81805,"task":"3D Face Reconstruction","parent_task":"3D","dataset":"AFLW2000-3D","model_name":"3DDFA","metrics":{"Mean NME ":"5.3695%"},"paper_url":"http://arxiv.org/abs/1511.07212v1","paper_title":"Face Alignment Across Large Poses: A 3D Solution","paper_date":"2015-11-23","code_links":[],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":81806,"task":"3D Face Reconstruction","parent_task":"3D","dataset":"AFLW2000-3D","model_name":"DeFA","metrics":{"Mean NME ":"5.6454%"},"paper_url":"http://arxiv.org/abs/1709.01442v1","paper_title":"Dense Face Alignment","paper_date":"2017-09-05","code_links":[{"title":"yaojieliu/ICCVW2017-DenseFaceAlignment","url":"https://github.com/yaojieliu/ICCVW2017-DenseFaceAlignment"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":81807,"task":"3D Face Reconstruction","parent_task":"3D","dataset":"AFLW2000-3D","model_name":"DSFNet-is","metrics":{"Mean NME":"3.16"},"paper_url":"https://arxiv.org/abs/2305.11522v1","paper_title":"DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment","paper_date":"2023-05-19","code_links":[{"title":"lhyfst/dsfnet","url":"https://github.com/lhyfst/dsfnet"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":91066,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"SADRNet","metrics":{"Mean NME ":"3.25%"},"paper_url":"https://arxiv.org/abs/2106.03021v1","paper_title":"SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction","paper_date":"2021-06-06","code_links":[{"title":"MCG-NJU/SADRNet","url":"https://github.com/MCG-NJU/SADRNet"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":91067,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"VGG-F","metrics":{"Mean NME ":"3.42%"},"paper_url":"https://arxiv.org/abs/2103.16554v2","paper_title":"Pre-training strategies and datasets for facial representation learning","paper_date":"2021-03-30","code_links":[{"title":"tomas-gajarsky/facetorch","url":"https://github.com/tomas-gajarsky/facetorch"},{"title":"1adrianb/unsupervised-face-representation","url":"https://github.com/1adrianb/unsupervised-face-representation"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":91068,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"B-spline FFD","metrics":{"Mean NME ":"3.51%"},"paper_url":"https://arxiv.org/abs/2105.14857v2","paper_title":"Learning Free-Form Deformation for 3D Face Reconstruction from In-The-Wild Images","paper_date":"2021-05-31","code_links":[],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":91069,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"3DDFA-V2","metrics":{"Mean NME ":"3.56%"},"paper_url":"https://arxiv.org/abs/2009.09960v2","paper_title":"Towards Fast, Accurate and Stable 3D Dense Face Alignment","paper_date":"2020-09-21","code_links":[{"title":"cleardusk/3DDFA","url":"https://github.com/cleardusk/3DDFA"},{"title":"cleardusk/3DDFA_V2","url":"https://github.com/cleardusk/3DDFA_V2"},{"title":"scoutant/face-blur","url":"https://github.com/scoutant/face-blur"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":91070,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"PRN","metrics":{"Mean NME ":"3.9625%"},"paper_url":"http://arxiv.org/abs/1803.07835v1","paper_title":"Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network","paper_date":"2018-03-21","code_links":[{"title":"YadiraF/PRNet","url":"https://github.com/YadiraF/PRNet"},{"title":"jimmy0087/faceai-master","url":"https://github.com/jimmy0087/faceai-master"},{"title":"minoring/PRNet","url":"https://github.com/minoring/PRNet"},{"title":"heathentw/prnet-tf2","url":"https://github.com/heathentw/prnet-tf2"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":91071,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"3DDFA","metrics":{"Mean NME ":"5.3695%"},"paper_url":"http://arxiv.org/abs/1511.07212v1","paper_title":"Face Alignment Across Large Poses: A 3D Solution","paper_date":"2015-11-23","code_links":[],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":91072,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"DeFA","metrics":{"Mean NME ":"5.6454%"},"paper_url":"http://arxiv.org/abs/1709.01442v1","paper_title":"Dense Face Alignment","paper_date":"2017-09-05","code_links":[{"title":"yaojieliu/ICCVW2017-DenseFaceAlignment","url":"https://github.com/yaojieliu/ICCVW2017-DenseFaceAlignment"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":91073,"task":"3D Face Reconstruction","parent_task":"Face Reconstruction","dataset":"AFLW2000-3D","model_name":"DSFNet-is","metrics":{"Mean NME":"3.16"},"paper_url":"https://arxiv.org/abs/2305.11522v1","paper_title":"DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment","paper_date":"2023-05-19","code_links":[{"title":"lhyfst/dsfnet","url":"https://github.com/lhyfst/dsfnet"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":104166,"task":"3D Face Reconstruction","parent_task":null,"dataset":"AFLW2000-3D","model_name":"SADRNet","metrics":{"Mean NME ":"3.25%"},"paper_url":"https://arxiv.org/abs/2106.03021v1","paper_title":"SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction","paper_date":"2021-06-06","code_links":[{"title":"MCG-NJU/SADRNet","url":"https://github.com/MCG-NJU/SADRNet"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":104167,"task":"3D Face Reconstruction","parent_task":null,"dataset":"AFLW2000-3D","model_name":"VGG-F","metrics":{"Mean NME ":"3.42%"},"paper_url":"https://arxiv.org/abs/2103.16554v2","paper_title":"Pre-training strategies and datasets for facial representation learning","paper_date":"2021-03-30","code_links":[{"title":"tomas-gajarsky/facetorch","url":"https://github.com/tomas-gajarsky/facetorch"},{"title":"1adrianb/unsupervised-face-representation","url":"https://github.com/1adrianb/unsupervised-face-representation"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":104168,"task":"3D Face Reconstruction","parent_task":null,"dataset":"AFLW2000-3D","model_name":"B-spline FFD","metrics":{"Mean NME ":"3.51%"},"paper_url":"https://arxiv.org/abs/2105.14857v2","paper_title":"Learning Free-Form Deformation for 3D Face Reconstruction from In-The-Wild Images","paper_date":"2021-05-31","code_links":[],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":104169,"task":"3D Face Reconstruction","parent_task":null,"dataset":"AFLW2000-3D","model_name":"3DDFA-V2","metrics":{"Mean NME ":"3.56%"},"paper_url":"https://arxiv.org/abs/2009.09960v2","paper_title":"Towards Fast, Accurate and Stable 3D Dense Face Alignment","paper_date":"2020-09-21","code_links":[{"title":"cleardusk/3DDFA","url":"https://github.com/cleardusk/3DDFA"},{"title":"cleardusk/3DDFA_V2","url":"https://github.com/cleardusk/3DDFA_V2"},{"title":"scoutant/face-blur","url":"https://github.com/scoutant/face-blur"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":104170,"task":"3D Face Reconstruction","parent_task":null,"dataset":"AFLW2000-3D","model_name":"PRN","metrics":{"Mean NME ":"3.9625%"},"paper_url":"http://arxiv.org/abs/1803.07835v1","paper_title":"Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network","paper_date":"2018-03-21","code_links":[{"title":"YadiraF/PRNet","url":"https://github.com/YadiraF/PRNet"},{"title":"jimmy0087/faceai-master","url":"https://github.com/jimmy0087/faceai-master"},{"title":"minoring/PRNet","url":"https://github.com/minoring/PRNet"},{"title":"heathentw/prnet-tf2","url":"https://github.com/heathentw/prnet-tf2"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":104171,"task":"3D Face Reconstruction","parent_task":null,"dataset":"AFLW2000-3D","model_name":"3DDFA","metrics":{"Mean NME ":"5.3695%"},"paper_url":"http://arxiv.org/abs/1511.07212v1","paper_title":"Face Alignment Across Large Poses: A 3D Solution","paper_date":"2015-11-23","code_links":[],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":104172,"task":"3D Face Reconstruction","parent_task":null,"dataset":"AFLW2000-3D","model_name":"DeFA","metrics":{"Mean NME ":"5.6454%"},"paper_url":"http://arxiv.org/abs/1709.01442v1","paper_title":"Dense Face Alignment","paper_date":"2017-09-05","code_links":[{"title":"yaojieliu/ICCVW2017-DenseFaceAlignment","url":"https://github.com/yaojieliu/ICCVW2017-DenseFaceAlignment"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]},{"id":104173,"task":"3D Face Reconstruction","parent_task":null,"dataset":"AFLW2000-3D","model_name":"DSFNet-is","metrics":{"Mean NME":"3.16"},"paper_url":"https://arxiv.org/abs/2305.11522v1","paper_title":"DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment","paper_date":"2023-05-19","code_links":[{"title":"lhyfst/dsfnet","url":"https://github.com/lhyfst/dsfnet"}],"metrics_order":"[\"Mean NME \", \"Mean NME\"]","area":"Computer Vision","uses_additional_data":0,"source":"archive","tags":[]}]}