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Guided Face Synthesis for Face Recognition

Our pre-trained CFSMs could be a plug-in to any SoTA Face recognition model. Here, we provide a training example based on the ArcFace Pytorch repo.

Training

  • Prepare the training data and add the data path to the configuration file.
  • Train the model:
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python -m torch.distributed.launch \
--nproc_per_node=8 \
--nnodes=1 \
--node_rank=0 \
--master_addr="127.0.0.1" \
--master_port=12348 train.py configs/arcface_ms1mv2_r50_ours

Trained Models

  • Pre-trained face synthesis model

    In order to train the synthesis model for face recognition, 70K images of faces from WiderFace are used as target data. The pre-trained model could be downloaded here.

  • Trained face recognition models

Method Arch Train Dataset Link
ArcFace+CFSM R50 MS1MV2 gdrive, baidudrive (wyiv)
AdaFace+CFSM R100 WebFace12M gdrive, baidudrive (hatp)

Validation

  • IJB-B dataset

    Method Arch Train Dataset TAR@FAR=0.001% TAR@FAR=0.01% TAR@FAR=0.1% Rank1 Rank5
    ArcFace R50 MS1MV2 87.26 94.01 95.95 94.61 96.52
    ArcFace+CFSM R50 MS1MV2 90.95 94.61 96.21 94.96 96.84

  • IJB-C dataset

    Method Arch Train Dataset TAR@FAR=0.0001% TAR@FAR=0.001% TAR@FAR=0.01% Rank1 Rank5
    ArcFace R50 MS1MV2 87.24 93.32 95.61 95.89 97.08
    ArcFace+CFSM R50 MS1MV2 89.34 94.06 95.90 96.31 97.48

  • TinyFace dataset

    Method Arch Train Dataset Rank1 Rank5
    ArcFace R50 MS1MV2 62.21 66.85
    ArcFace+CFSM R50 MS1MV2 63.01 68.21
    AdaFace R100 WebFace12M 72.29 74.97
    AdaFace+CFSM R100 WebFace12M 73.87 76.77

  • IJB-S dataset

Method Arch Train Dataset V2S Rank1 V2S Rank5 V2S 1% V2S 10% V2B Rank1 V2B Rank5 V2B 1% V2B 10% V2V Rank1 V2V Rank5 V2V 1% V2V 10%
ArcFace R50 MS1MV2 58.78 66.40 40.99 50.45 60.66 67.43 43.12 51.38 14.81 26.72 2.51 5.72
ArcFace+CFSM R50 MS1MV2 63.86 69.95 47.86 56.44 65.95 71.16 47.28 57.24 21.38 35.11 2.96 7.41
AdaFace R100 WebFace12M 71.35 76.24 59.40 66.34 71.93 76.56 59.37 66.68 36.71 50.03 4.62 11.84
AdaFace+CFSM R100 WebFace12M 72.54 77.59 60.94 66.02 72.65 78.18 60.26 65.88 39.14 50.91 5.05 13.17