A new model for camera noise based on normalizing flows

Generating images from object detection layouts via VQ-VAE and a Transformer

Virtual try-on (garment transfer) in varied poses from a new dataset of dancing videos

GAN for generating photorealistic humans with controllable clothing

Improved pretraining for vision transformers based on formula-generated synthetic fractal images

New approach to training on a mixture of synthetic and real data for crowd counting

New synthetic dataset used to train a state of the art model for eyeglass removal

Generating synthetic samples to improve few-shot learning

3D reconstruction of hand-held objects from a single RGB image without knowing their 3D templates.

An extensible library for generating 3D synthetic data with Blender that just works.

StyleGAN2-ADA: adaptive discriminator augmentation that helps use StyleGAN2 with small datasets

The original StyleGAN from NVIDIA allowing to mix and match facial features at multiple levels

The original progressively growing GAN from NVIDIA

StyleGAN3: making StyleGAN translation and rotation invariant

The original paper on GANs

StyleGAN2: fixing several shortcomings of StyleGAN and taking it one step further

Classical GAN for superresolution

First successful convolutional GAN for generating images

Large-scale GANs for generating varied class-conditional images, with hundreds of classes

pix2pix: first GAN-based style transfer model for paired data

CycleGAN: style transfer without paired data via cycle consistency

AdaIN: a simple and very powerful idea for neural style transfer

A new weight normalization technique that generally improves GAN training

Bidirectional GANs that learn to generate new samples and extract features at the same time

Superresolution GAN improved in both architecture and loss functions

pix2pixHD: high-resolution style transfer for paired datasets

FUNIT: style transfer with styles defined by a few sample images

MUNIT: disentangling style and content for style transfer

Real-SR improved with better discriminators and synthetically generated data

Learning degradation kernels for superresolution with kernel prediction networks

KernelGAN: adversarial training of downscaling kernels for superresolution

ZSSR: learning downscaling kernels for superresolution from a single image

Head pose estimation model trained on synthetic data with syn-to-real domain adaptation

A new benchmark for synthetic-to-real domain adaptation

Joint alignment of synthetic and real domains for robotics

A new technique to bridge source and target domains in adversarial domain adaptation

Object tracking with strong domain generalization capabilities

Classification and survey of visual domain adaptation techniques, >200 references

Domain adaptation with Siamese networks

Domain adaptation based on optimal transport

In this paper, we propose a new assumption, generalized label shift (GLS), to improve robustness against mismatched label distributions