calls UNIT “Choose for unpaired translation using a shared latent space, an alternative to CycleGAN's cycle consistency.”
Image-to-Image Translation in PyTorch
UNIT is queued for analysis. Crawling candidates and ranking them takes a few minutes. This page updates itself when the list exists — you can also come back later.
What is known so far comes from the other direction:
These projects were analysed and named UNIT among their alternatives. The relationship is not symmetric — how UNIT rates them is a separate judgement, made when UNIT is analysed in its own right.
calls UNIT “Choose for unpaired translation using a shared latent space, an alternative to CycleGAN's cycle consistency.”
Image-to-Image Translation in PyTorch
calls UNIT “when you need unsupervised translation using a shared latent space assumption.”
Image-to-image translation with conditional adversarial nets
calls UNIT “Unsupervised unpaired image translation with shared latent space; earlier model useful for simple unpaired-domain translation.”
Synthesizing and manipulating 2048x1024 images with conditional GANs
calls UNIT “Choose when you specifically need the older shared-latent-space UNIT baseline for unpaired translation; it is more limited and unmaintained compared with CycleGAN.”
Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
calls UNIT “Choose for classic unsupervised image translation if you prefer the original UNIT implementation in PyTorch.”
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.