Feature Quantization Improves GAN Training
YangNaruto/FQ-GAN
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ICML 2020
The instability in GAN training has been a long-standing problem despite remarkable research efforts.
InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs
In this work, we propose a framework called InterFaceGAN to interpret the disentangled face representation learned by the state-of-the-art GAN models and study the properties of the facial semantics encoded in the latent space.
Fine-Tuning StyleGAN2 For Cartoon Face Generation
happy-jihye/Cartoon-StyleGan2
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Although existing models can generate realistic target images, it's difficult to maintain the structure of the source image.
Complete Face Recovery GAN: Unsupervised Joint Face Rotation and De-Occlusion From a Single-View Image
yeongjoonJu/CFR-GAN
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Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2022
In addition, the lack of high-quality paired data remains an obstacle for both methods.
Controllable and Guided Face Synthesis for Unconstrained Face Recognition
To address this problem, we propose a controllable face synthesis model (CFSM) that can mimic the distribution of target datasets in a style latent space.
StyleNAT: Giving Each Head a New Perspective
Image generation has been a long sought-after but challenging task, and performing the generation task in an efficient manner is similarly difficult.
A Comprehensive Survey on Pose-Invariant Face Recognition
The capacity to recognize faces under varied poses is a fundamental human ability that presents a unique challenge for computer vision systems.
A Multiresolution 3D Morphable Face Model and Fitting Framework
In this paper, we present the Surrey Face Model, a multi-resolution 3D Morphable Model that we make available to the public for non-commercial purposes.
Multi-Agent Diverse Generative Adversarial Networks
Daeijavad/MAD-GAN
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CVPR 2018
Second, to enforce that different generators capture diverse high probability modes, the discriminator of MAD-GAN is designed such that along with finding the real and fake samples, it is also required to identify the generator that generated the given fake sample.
Face Synthesis from Visual Attributes via Sketch using Conditional VAEs and GANs
DetionDX/Attribute2Sketch2Face
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In this paper, we take a different approach, where we formulate the original problem as a stage-wise learning problem.