pi-GAN-pytorch
pytorch-CycleGAN-and-pix2pix
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| pi-GAN-pytorch | pytorch-CycleGAN-and-pix2pix | |
|---|---|---|
| 1 | 10 | |
| 114 | 21,998 | |
| - | - | |
| 0.0 | 2.8 | |
| about 3 years ago | 2 days ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
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pi-GAN-pytorch
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[R] AI Researchers From Stanford University Unveils pi-GAN: A Novel Periodic Implicit GAN For 3D-Aware Image Synthesis (Paper, Code included)
Code for https://arxiv.org/abs/2012.00926 found: https://github.com/lucidrains/pi-GAN-pytorch
pytorch-CycleGAN-and-pix2pix
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List of AI-Models
Click to Learn more...
- I want an A.I. to learn my art style so I can keep making art in my art style despite not having the time to do it.
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I'm looking for an AI Art generator from images
pix2pix (https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix) - This is a PyTorch implementation of the pix2pix algorithm for image-to-image translation. Given a set of images, the model can learn to generate a new image from a different domain that is similar to the input image.
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Seamless textures with SD and PBR maps with a pix2pix cGAN
Using junyanz/pytorch-CycleGAN-and-pix2pix as a basis for pix2pix, I applied the same blending method to fix seams. It essentially takes an input image and generates an output. The results depend on the paired training data. In this case, each map (height, roughness, etc.) is a separate checkpoint and had to be trained on paired training data with the diffuse as the input and the respective map as the output.
- IA art
- Segmentation and clasification with UNET
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Trying to understand PatchGAN discriminator
Code for https://arxiv.org/abs/1611.07004 found: https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
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I made a 3d topographic map based on my recent civ6 game
pix2pix algorithm is used for translating Civ6Maps to heightmaps. Synthesized terrain was rendered in blender.
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This Wojak Does Not Exist
https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
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Training a neural net to generate Wojaks
I'm working on creating a face-to-wojak model using PyTorch CycleGan/Pix2Pix [0] and found some of my outputs to be outrageous yet somehow relatable. People are into it so thought I'd share on HN
[0] https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
What are some alternatives?
lightweight-gan - Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two
pix2pixHD - Synthesizing and manipulating 2048x1024 images with conditional GANs
nerf - Code release for NeRF (Neural Radiance Fields)
generative-inpainting-pytorch - A PyTorch reimplementation for paper Generative Image Inpainting with Contextual Attention (https://arxiv.org/abs/1801.07892)
CIPS-3D - 3D-aware GANs based on NeRF (arXiv).
pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
DeblurGANv2 - [ICCV 2019] "DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better" by Orest Kupyn, Tetiana Martyniuk, Junru Wu, Zhangyang Wang
Deep-Fakes
nerfmm - (Arxiv 2021) NeRF--: Neural Radiance Fields Without Known Camera Parameters
AnimeGAN - Generating Anime Images by Implementing Deep Convolutional Generative Adversarial Networks paper
Papers-in-100-Lines-of-Code - Implementation of papers in 100 lines of code.
PaddleGAN - 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.