RetinaFace: Single-stage Dense Face Localisation in the Wild.

Though tremendous strides have been made in uncontrolled face detection, accurate and efficient face localisation in the wild remains an open challenge.

This paper presents a robust single-stage face detector, named RetinaFace, which performs pixel-wise face localisation on various scales of faces by taking advantages of joint extra-supervised and self-supervised multi-task learning.


Paper: https://lnkd.in/dF48muv
#deeplearning #facerecognition #research

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Deepfakes were a crazy creation of the #GANs so here is an answer about their detection.

Recurrent-Convolution Approach to DeepFake Detection - State-Of-Art Results on FaceForensics++

Spread of misinformation has become a significant problem, raising the importance of relevant detection methods.

While there are different manifestations of misinformation, in this work we focus on detecting face manipulations in videos.

Here the authors attempt to detect Deepfake, Face2Face and FaceSwap manipulations in videos.

Paper: arxiv.org/abs/1905.00582
Code: Adding soon

#deeplearning
#facerecognition
✴️ @AI_Python_EN