zdyshine / imaginaire

NVIDIA PyTorch GAN library with distributed and mixed precision support

Home Page:http://imaginaire.cc/

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Imaginaire

Docs | License | Installation | Model Zoo

Imaginaire is a pytorch library that contains optimized implementation of several image and video synthesis methods developed at NVIDIA.

License

Imaginaire is released under NVIDIA Software license. For commercial use, please consult researchinquiries@nvidia.com

What's inside?

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We have a tutorial for each model. Click on the model name, and your browser should take you to the tutorial page for the project.

Supervised Image-to-Image Translation

Algorithm Name Feature Publication
pix2pixHD Learn a mapping that converts a semantic image to a high-resolution photorealistic image. Wang et. al. CVPR 2018
SPADE Improve pix2pixHD on handling diverse input labels and delivering better output quality. Park et. al. CVPR 2019

Unsupervised Image-to-Image Translation

Algorithm Name Feature Publication
UNIT Learn a one-to-one mapping between two visual domains. Liu et. al. NeurIPS 2017
MUNIT Learn a many-to-many mapping between two visual domains. Huang et. al. ECCV 2018
FUNIT Learn a style-guided image translation model that can generate translations in unseen domains. Liu et. al. ICCV 2019
COCO-FUNIT Improve FUNIT with a content-conditioned style encoding scheme for style code computation. Saito et. al. ECCV 2020

Video-to-video Translation

Algorithm Name Feature Publication
vid2vid Learn a mapping that converts a semantic video to a photorealistic video. Wang et. al. NeurIPS 2018
fs-vid2vid Learn a subject-agnostic mapping that converts a semantic video and an example image to a photoreslitic video. Wang et. al. NeurIPS 2019
wc-vid2vid Improve vid2vid on view consistency and long-term consistency. Mallya et. al. ECCV 2020

About

NVIDIA PyTorch GAN library with distributed and mixed precision support

http://imaginaire.cc/

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Language:Python 99.0%Language:Shell 0.9%Language:Batchfile 0.1%