SLNo | Architecture_Block_Diagram | Model | PaperLink | GitHub | Dataset | Framework | Year | Training Pipeline | Testing Pipeline | Loss | License | Keywords | ||
1 | FaRL-B | General Facial Representation Learning in a Visual-Linguistic Manner |
https://github.com/FacePerceiver/FaRL | LaPa CelebAMask-HQ | Pytorch | 2021 | Yes | NA | Contrastive, Binary cross entropy | MIT | ||||
2 | DML-CSR | Decoupled Multi-task Learning with Cyclical Self-Regulation for Face Parsing |
https://github.com/deepinsight/insightface | Helen LaPa CelebAMask-HQ | Pytorch | 2022 | Yes | Yes | Consistency, Lovasz Softmax, KL Divergence | MIT | ||||
3 | EAGRNet | Edge-aware Graph Representation Learning and Reasoning for Face Parsing |
https://github.com/tegusi/EAGRNet | Helen LaPa CelebAMask-HQ | Pytorch | 2021 | Yes | Yes(eval) | BA(boundary attention) loss, Cross entropy loss | NA | ||||
4 | RT-Net | RoI Tanh-polar Transformer Network for Face Parsing in the Wild |
https://github.com/hhj1897/face_parsing | LaPa iBugMask | Pytorch | 2021 | NA | Yes | Cross entropy loss, Dice loss | MIT | ||||
5 | AGRNet | AGRNet: Adaptive Graph Representation Learning and Reasoning for Face Parsing |
NA | LaPa Helen(merged cls) CelebAMask-HQ | NA | 2021 | NA | NA | Cross Entropy loss, BA Loss, Discriminative loss | NA | ||||
6 | UNet(real) | Fake It Till You Make It: Face analysis in the wild using synthetic data alone |
NA | Helen LaPa | NA | 2021 | NA | NA | BCE Loss | Custom | ||||
7 | UNet(synthetic) | Fake It Till You Make It: Face analysis in the wild using synthetic data alone |
NA | LaPa Helen | NA | 2021 | NA | NA | BCE Loss | Custom | ||||
8 | AFIP | Accurate facial image parsing at real-time speed |
NA | LaPa CelebAMask-HQ | NA | 2019 | NA | NA | SC Loss(Statistical Contextual loss) | NA | ||||
9 | EHANet | EHANet: An Effective Hierarchical Aggregation Network for Face Parsing |
https://github.com/JACKYLUO1991/FaceParsing | CelebAMask-HQ LaPa Helen | Pytorch | 2020 | Yes | Yes | Boundary Aware loss | MIT |