pi-GAN-pytorch
DeblurGANv2
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| pi-GAN-pytorch | DeblurGANv2 | |
|---|---|---|
| 1 | 1 | |
| 114 | 976 | |
| - | 2.8% | |
| 0.0 | 0.0 | |
| about 3 years ago | almost 2 years 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
DeblurGANv2
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Implementing a CNN on an FPGA
I am trying to implement an image deblurring model (DeblurGANv2) The generator takes blurred images as an input and outputs the corrected image, the discriminator helps in training the generator. The model has been trained and I have run and deblurred images on a GPU. I am completely new to the domain of Machine learning and I am trying to implement this on an FPGA. I wanted your guys help on how to do this. The .h5 files contains the weights of the NN, how do I figure out its structure and put it on my FPGA. Can you please suggest some tools that might help or github links for people who have implemented similar stuff.
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)
Pix2Vox - The official implementation of "Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images". (Xie et al., ICCV 2019)
CIPS-3D - 3D-aware GANs based on NeRF (arXiv).
XVFI - [ICCV 2021, Oral 3%] Official repository of XVFI
nerfmm - (Arxiv 2021) NeRF--: Neural Radiance Fields Without Known Camera Parameters
NAFNet - The state-of-the-art image restoration model without nonlinear activation functions.
Papers-in-100-Lines-of-Code - Implementation of papers in 100 lines of code.
Ghost-DeblurGAN - This is a lightweight GAN developed for real-time deblurring. The model has a super tiny size and a rapid inference time. The motivation is to boost marker detection in robotic applications, however, you may use it for other applications definitely.
giraffe - This repository contains the code for the CVPR 2021 paper "GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields"
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch