Image Colourization using Conditional Generative Adversarial Network

Implementation of some types of GANs (Deep convolutional GAN - Wasserstein GAN - conditional GAN) with PyTorch library

Use conditional-dcgans to generate realistic images of digits

Conditional Cycle-Consistent Generative Adversarial Networks (CCycleGAN)

Text to image synthesis with GAN-CLS and MSGAN

Datasets, code and models from our driver gaze estimation works over the last few years.

CGAN ProjectionCGAN ACGAN InfoGAN Pytorch

[NeurIPS 2022, T-PAMI 2023] Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models

[CVPR 2020] GAN Compression: Efficient Architectures for Interactive Conditional GANs