Face Generation
137 papers with code • 0 benchmarks • 4 datasets
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.
( Image credit: Progressive Growing of GANs for Improved Quality, Stability, and Variation )
Benchmarks
These leaderboards are used to track progress in Face Generation
Libraries
Use these libraries to find Face Generation models and implementations
iFakeFaceDB
DFDM
VGGFace2 HQ
Face dataset by Generated Photos
Subtasks
Most implemented papers
Progressive Growing of GANs for Improved Quality, Stability, and Variation
tkarras/progressive_growing_of_gans
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ICLR 2018
We describe a new training methodology for generative adversarial networks.
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
deepinsight/insightface
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CVPR 2019
Recently, a popular line of research in face recognition is adopting margins in the well-established softmax loss function to maximize class separability.
Everybody Dance Now
carolineec/EverybodyDanceNow
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ICCV 2019
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.
FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping
We propose a novel attributes encoder for extracting multi-level target face attributes, and a new generator with carefully designed Adaptive Attentional Denormalization (AAD) layers to adaptively integrate the identity and the attributes for face synthesis.
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
eladrich/pixel2style2pixel
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CVPR 2021
We present a generic image-to-image translation framework, pixel2style2pixel (pSp).
Learning a model of facial shape and expression from 4D scans
Rubikplayer/flame-fitting
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SIGGRAPH Asia 2017
FLAME is low-dimensional but more expressive than the FaceWarehouse model and the Basel Face Model.
GANimation: Anatomically-aware Facial Animation from a Single Image
albertpumarola/GANimation
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ECCV 2018
Recent advances in Generative Adversarial Networks (GANs) have shown impressive results for task of facial expression synthesis.
Interpreting the Latent Space of GANs for Semantic Face Editing
genforce/interfacegan
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CVPR 2020
In this work, we propose a novel framework, called InterFaceGAN, for semantic face editing by interpreting the latent semantics learned by GANs.
Few-shot Knowledge Transfer for Fine-grained Cartoon Face Generation
minivision-ai/photo2cartoon
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In this paper, we are interested in generating fine-grained cartoon faces for various groups.
Wav2Pix: Speech-conditioned Face Generation using Generative Adversarial Networks
Speech is a rich biometric signal that contains information about the identity, gender and emotional state of the speaker.
