30.09.2019 · Training a face Recognizer using ResNet50 + ArcFace in TensorFlow 2.0 The aim of this project is to train a state of art face recognizer using TensorFlow 2.0. The architecture chosen is a modified version of ResNet50 and the loss function used is ArcFace, both originally developed by deepinsight in mxnet.
arcface-pytorch / models / resnet.py / Jump to. Code definitions. conv3x3 Function BasicBlock Class __init__ Function forward Function IRBlock Class __init__ Function forward Function Bottleneck Class __init__ Function forward Function SEBlock Class __init__ Function forward Function ResNetFace Class __init__ Function _make_layer Function ...
Verification performance (%) of ArcFace using ResNet- 101 [44] trained on VGGFace2 [42] and VGGFace2 8631 Races with syntesised images of non-Caucasian subjects ...
arcface-insightface : Arcface model (Resnet100 backbone) from Insightface. resnet50-msceleb-arcface-2021 : Resnet Arcface model trained with MSCeleb dataset ...
ResNet-100 is used for training. ... As reported in Table4, sub-center ArcFace trained on noisy MS1MV0 achieves comparable performance compared to ArcFace ...
arcface-pytorch / models / resnet.py / Jump to. Code definitions. conv3x3 Function BasicBlock Class __init__ Function forward Function IRBlock Class __init__ Function ...
In this paper, we propose an Additive Angular Margin Loss (ArcFace) to obtain highly discriminative features for face recognition. The proposed ArcFace has ...
Sep 30, 2019 · The architecture chosen is a modified version of ResNet50 and the loss function used is ArcFace, both originally developed by deepinsight in mxnet. The dataset used for training is the CASIA-Webface MS1M-ArcFace dataset used in insightface, and it is available their dataset zoo. The images are aligned using mtcnn and cropped to 112x112.