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serengil / deepface

A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
https://www.youtube.com/watch?v=WnUVYQP4h44&list=PLsS_1RYmYQQFdWqxQggXHynP1rqaYXv_E&index=1
MIT License
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Request for documentation on Face Recognition models architectures and training datasets #1367

Open HectorPenades opened 10 hours ago

HectorPenades commented 10 hours ago

Description

Dear DeepFace Team,

I hope this message finds you well. I would like to kindly request documentation on the specific models and weights used in DeepFace for face recognition. Could you provide details on the exact architectures (e.g. VGG, Inception, DNN, Resnet34, ResNet 50, ResNet100, ...) and the training datasets (e.g., MS1M-Celeb, VGGFace2, CASIA-WebFace, etc.) used for each model integrated into DeepFace? This would greatly help the community understand the underlying implementations and facilitate more accurate comparisons in research.

Thank you for your consideration, and I look forward to your response.

HectorPenades commented 10 hours ago

I will add in this comment the information that I am finding:

CONFIRMED

NOT CONFIRMED ArcFace: ResNet34, CASIA-WebFace, 40 E - Link: https://github.com/leondgarse/Keras_insightface FaceNet: Inception, CASIA-WebFace or VGGFace2, X E - Link: https://github.com/davidsandberg/facenet VGG-Face: VGG-16, VGG-Face

PENDING Facenet512: Inception OpenFace: DeepFace: DNN, Facebook Dataset DeepID: DNN, CelebFaces+ / WDRef ArcFace: ResNet34, CASIA-WebFace Dlib: SFace: GhostFaceNet: GhostNet