generative-inpainting-pytorch VS co-mod-gan

Compare generative-inpainting-pytorch vs co-mod-gan and see what are their differences.

generative-inpainting-pytorch

A PyTorch reimplementation for paper Generative Image Inpainting with Contextual Attention (https://arxiv.org/abs/1801.07892) (by daa233)

co-mod-gan

[ICLR 2021, Spotlight] Large Scale Image Completion via Co-Modulated Generative Adversarial Networks (by zsyzzsoft)
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generative-inpainting-pytorch co-mod-gan
1 1
449 431
- -
1.8 1.8
about 3 years ago over 2 years ago
Python Python
MIT License GNU General Public License v3.0 or later
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generative-inpainting-pytorch

Posts with mentions or reviews of generative-inpainting-pytorch. We have used some of these posts to build our list of alternatives and similar projects.

co-mod-gan

Posts with mentions or reviews of co-mod-gan. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing generative-inpainting-pytorch and co-mod-gan you can also consider the following projects:

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

DeepCreamPy - Decensoring Hentai with Deep Neural Networks

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

ContraD - Code for the paper "Training GANs with Stronger Augmentations via Contrastive Discriminator" (ICLR 2021)

pix2pixHD - Synthesizing and manipulating 2048x1024 images with conditional GANs

Fast-SRGAN - A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps

ALAE - [CVPR2020] Adversarial Latent Autoencoders

Bringing-Old-Photos-Back-to-Life - Bringing Old Photo Back to Life (CVPR 2020 oral)

edge-connect - EdgeConnect: Structure Guided Image Inpainting using Edge Prediction, ICCV 2019 https://arxiv.org/abs/1901.00212

PEN-Net-for-Inpainting - [CVPR'2019] PEN-Net: Learning Pyramid-Context Encoder Network for High-Quality Image Inpainting

TFill - [CVPR 2022]: Bridging Global Context Interactions for High-Fidelity Image Completion