calls MUNIT “Choose for multimodal unpaired translation, offering multiple diverse outputs per input unlike CycleGAN.”
Image-to-Image Translation in PyTorch
MUNIT 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 MUNIT among their alternatives. The relationship is not symmetric — how MUNIT rates them is a separate judgement, made when MUNIT is analysed in its own right.
calls MUNIT “Choose for multimodal unpaired translation, offering multiple diverse outputs per input unlike CycleGAN.”
Image-to-Image Translation in PyTorch
calls MUNIT “Choose when you need multiple diverse outputs for the same unpaired image-to-image translation task, at the cost of an older, less maintained codebase.”
Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
calls MUNIT “when you need multimodal outputs in unsupervised image-to-image translation.”
Image-to-image translation with conditional adversarial nets
calls MUNIT “Unsupervised multimodal image-to-image translation; choose when you have unpaired domains and want diverse outputs rather than paired label-map supervision.”
Synthesizing and manipulating 2048x1024 images with conditional GANs
calls MUNIT “Choose for multimodal unsupervised image translation with a lightweight single-purpose PyTorch implementation.”
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.