GitHub - MathsShen/SCF: Spherical Confidence Learning for Face Recognition, accepted to CVPR2021 (Oral). (original) (raw)

This repository contains the PyTorch implementation of Sphere Confidence Face (SCF) proposed in the CVPR2021 oral paper:

Shen Li, Jianqing Xu, Xiaqing Xu, Pengcheng Shen, Shaoxin Li, and Bryan Hooi. Spherical Confidence Learning for Face Recognition, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021 (Oral).

Appendices can be found here: Appendices.

Empirical Results

IJB-B ResNet100 1e-5 ResNet100 1e-4 IJB-C ResNet100 1e-5 ResNet100 1e-4
CosFace 89.81 94.59 CosFace 93.86 95.95
+ PFE-G 89.96 94.64 + PFE-G 94.09 96.04
+ PFE-v N/A N/A + PFE-v N/A N/A
+ SCF-G 89.97 94.56 + SCF-G 94.15 96.02
+ SCF 91.02 94.95 + SCF 94.78 96.22
ArcFace 89.33 94.20 ArcFace 93.15 95.60
+ PFE-G 89.55 94.30 + PFE-G 92.95 95.32
+ PFE-v N/A N/A + PFE-v N/A N/A
+ SCF-G 89.52 94.24 + SCF-G 93.85 95.33
+ SCF 90.68 94.74 + SCF 94.04 96.09

Requirements

Getting Started

Training

Training consists of two separate steps:

  1. Train ResNet100 imported from backbones.py as the deterministic backbone using spherical loss, e.g. ArcFace loss.
  2. Train SCF based on the pretrained backbone by specifying the arguments including [GPU_IDS], [OUTPUT_DIR], [PATH_BACKBONE_CKPT] (the path of the pretrained backbone checkpoint) and [PATH_FC_CKPT] (the path of the pretrained fc-layer checkpoint) and then running the command:

python train.py
--dataset "ms1m"
--seed 777
--gpu_ids [GPU_IDS]
--batch_size 1024
--output_dir [OUTPUT_DIR]
--saved_bkb [PATH_BACKBONE_CKPT]
--saved_fc [PATH_FC_CKPT]
--num_workers 8
--epochs 30
--lr 3e-5
--lr_scheduler "StepLR"
--step_size 2
--gamma 0.5
--convf_dim 25088
--z_dim 512
--radius 64
--max_grad_clip 0
--max_grad_norm 0
--tensorboard

Test

IJB benchmark: use kappa\kappakappa as confidence score for each face image to aggregate representations as in Eqn (14). Refer to the standard IJB benchmark for implementation.

1v1 verification benchmark: use Eqn (13) as the similarity score.

Other Implementations

SCF in TFace: SCF

Citation

@inproceedings{li2021spherical,
  title={Spherical Confidence Learning for Face Recognition},
  author={Li, Shen and Xu, Jianqing and Xu, Xiaqing and Shen, Pengcheng and Li, Shaoxin and Hooi, Bryan},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={15629--15637},
  year={2021}
}