Face Generation
Face generation is the task of generating (or interpolating) new faces from an existing dataset.
The state-of-the-art results for this task are located in the Image Generation parent.
State-of-the-art leaderboards
| Trend | Dataset | Best Method | Paper title | Paper | Code | Compare |
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Subtasks
Greatest papers with code
Progressive Growing of GANs for Improved Quality, Stability, and Variation
We describe a new training methodology for generative adversarial networks.
SOTA for Image Generation on CIFAR-10
GANimation: Anatomically-aware Facial Animation from a Single Image
ECCV 2018
• albertpumarola/GANimation
• 
Recent advances in Generative Adversarial Networks (GANs) have shown impressive results for task of facial expression synthesis.
CONDITIONAL IMAGE GENERATION FACE GENERATION IMAGE-TO-IMAGE TRANSLATION
Talking Face Generation by Adversarially Disentangled Audio-Visual Representation
• Hangz-nju-cuhk/Talking-Face-Generation-DAVS
•
Talking face generation aims to synthesize a sequence of face images that correspond to a clip of speech.
Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition
• ZhaoJ9014/High_Performance_Face_Recognition
Benchmarking our model on one of the most popular unconstrained face recognition datasets IJB-C additionally verifies the promising generalizability of AIM in recognizing faces in the wild.
AGE-INVARIANT FACE RECOGNITION FACE GENERATION REPRESENTATION LEARNING
Face Synthesis for Eyeglass-Robust Face Recognition
A feasible method is to collect large-scale face images with eyeglasses for training deep learning methods.
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model
ECCV 2018
• barisgecer/facegan
• 
We propose a novel end-to-end semi-supervised adversarial framework to generate photorealistic face images of new identities with wide ranges of expressions, poses, and illuminations conditioned by a 3D morphable model.
DOMAIN ADAPTATION FACE GENERATION FACE RECOGNITION STYLE TRANSFER
Learning a model of facial shape and expression from 4D scans
SIGGRAPH Asia 2017
• Rubikplayer/flame-fitting
•
FLAME is low-dimensional but more expressive than the FaceWarehouse model and the Basel Face Model.
3D FACE ANIMATION 3D FACE MODELING 3D FACE RECONSTRUCTION FACE GENERATION
Everybody Dance Now
• Lotayou/everybody_dance_now_pytorch
•
This paper presents a simple method for "do as I do" motion transfer: given a source video of a person dancing we can transfer that performance to a novel (amateur) target after only a few minutes of the target subject performing standard moves.
Triple consistency loss for pairing distributions in GAN-based face synthesis
• ESanchezLozano/GANnotation
•
To show this is effective, we incorporate the triple consistency loss into the training of a new landmark-guided face to face synthesis, where, contrary to previous works, the generated images can simultaneously undergo a large transformation in both expression and pose.
CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training
ICLR 2018
• mkocaoglu/CausalGAN
•
We show that adversarial training can be used to learn a generative model with true observational and interventional distributions if the generator architecture is consistent with the given causal graph.