image-to-image translation
PyTorch implementation of CycleGAN and pix2pix for paired and unpaired image-to-image translation.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose when you need faster and memory-efficient unpaired translation via contrastive learning (CUT) rather than cycle consistency.
Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)
Choose for high-resolution (2048x1024) paired translation with more detailed output than standard pix2pix.
Synthesizing and manipulating 2048x1024 images with conditional GANs
Choose for unpaired translation using a shared latent space, an alternative to CycleGAN's cycle consistency.
Unsupervised Image-to-Image Translation
Choose for multimodal unpaired translation, offering multiple diverse outputs per input unlike CycleGAN.
Multimodal Unsupervised Image-to-Image Translation
Choose if you use PaddlePaddle and need a broad GAN library with image-to-image translation support.
PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, Wav2Lip, picture repair, image editing, photo2cartoon, image style transfer, GPEN, and so on.
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Choose if you must use TensorFlow for CycleGAN, but note it's outdated and unmaintained.
An implementation of CycleGan using TensorFlow
A collection of Keras GAN implementations including CycleGAN, but old and broader in scope.
Keras implementations of Generative Adversarial Networks.
A collection of PyTorch GAN implementations including the seed models, but educational and less maintained.
PyTorch implementations of Generative Adversarial Networks.
These projects were analysed and named pytorch-CycleGAN-and-pix2pix among their alternatives. The relationship is not symmetric — how pytorch-CycleGAN-and-pix2pix rates them is a separate judgement, made when pytorch-CycleGAN-and-pix2pix is analysed in its own right.
calls pytorch-CycleGAN-and-pix2pix “choose it for the canonical official implementation of CycleGAN/pix2pix if that specific task is your focus.”
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
calls pytorch-CycleGAN-and-pix2pix “Official lower-resolution pix2pix/CycleGAN codebase; choose for standard 256px paired or unpaired translation instead of HD semantic synthesis.”
Synthesizing and manipulating 2048x1024 images with conditional GANs