Disentangled and Controllable Face Image Generation via 3D Imitative-Contrastive Learning

Yu Deng, Jiaolong Yang, Dong Chen, Fang Wen, Xin Tong
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Figure 1 : This paper presents a face image synthesis approach that generates realistic face images of virtual people with independent latent variables of identity, expression, pose, and illumination. The latent space is interpretable and highly disentangled, which allows precise control of the targeted images (e.g., degree of each pose angle, lighting intensity and direction), as shown in the top row. The bottom row shows the generated images when we keep the identity and randomize other
more » ... ties. The faces generated by our method are not any real person in the world.
doi:10.1109/cvpr42600.2020.00520 dblp:conf/cvpr/DengYCWT20 fatcat:ijuehbe2v5gzlal5h6qsosgbju