OASIS VS pix2pixHD

Compare OASIS vs pix2pixHD and see what are their differences.

OASIS

Official implementation of the paper "You Only Need Adversarial Supervision for Semantic Image Synthesis" (ICLR 2021) (by boschresearch)
semantic-image-synthesis Gan image-to-image-translation Computer Vision multi-modal generative-adversarial-networks Deep Learning Pytorch image-generation label-to-image-translation oasis iclr2021 Machine Learning bcai
Source Code
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pix2pixHD

Synthesizing and manipulating 2048x1024 images with conditional GANs (by NVIDIA)
Gan Deep Learning deep-neural-networks Pytorch Pix2pix image-to-image-translation generative-adversarial-network Computer Vision computer-graphics
Source Code
tcwang0509.github.io
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OASIS pix2pixHD
1 6
317 6,530
2.5% 0.5%
10.0 0.0
over 1 year ago 12 months ago
Python Python
GNU Affero General Public License v3.0 GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

OASIS

Posts with mentions or reviews of OASIS. We have used some of these posts to build our list of alternatives and similar projects.
  • StyleGAN-NADA: Blind Training and Other Wonders
    1 project | dev.to | 7 Dec 2022
    Conclusion So this is how StyleGAN-NADA, a CLIP-guided zero-shot method for Non-Adversarial Domain Adaptation of image generators, works. Although the StyleGAN-NADA is focused on StyleGAN, it can be applied to other generative architectures such as OASIS and many others.

pix2pixHD

Posts with mentions or reviews of pix2pixHD. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-02-04.

What are some alternatives?

When comparing OASIS and pix2pixHD you can also consider the following projects:

Deep-Exemplar-based-Video-Colorization - The source code of CVPR 2019 paper "Deep Exemplar-based Video Colorization".

pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch

Keras-GAN - Keras implementations of Generative Adversarial Networks.

awesome-colab-notebooks - Collection of google colaboratory notebooks for fast and easy experiments

sofgan - [TOG 2022] SofGAN: A Portrait Image Generator with Dynamic Styling

AdamP - AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights (ICLR 2021)

face-parsing.PyTorch - Using modified BiSeNet for face parsing in PyTorch

clean-fid - PyTorch - FID calculation with proper image resizing and quantization steps [CVPR 2022]

generative-inpainting-pytorch - A PyTorch reimplementation for paper Generative Image Inpainting with Contextual Attention (https://arxiv.org/abs/1801.07892)

anycost-gan - [CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing

contrastive-unpaired-translation - Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)

OASIS vs Deep-Exemplar-based-Video-Colorization pix2pixHD vs pytorch-CycleGAN-and-pix2pix OASIS vs Keras-GAN pix2pixHD vs awesome-colab-notebooks OASIS vs pytorch-CycleGAN-and-pix2pix pix2pixHD vs sofgan OASIS vs AdamP pix2pixHD vs face-parsing.PyTorch OASIS vs clean-fid pix2pixHD vs generative-inpainting-pytorch OASIS vs anycost-gan pix2pixHD vs contrastive-unpaired-translation