DeblurGANv2
XVFI
| DeblurGANv2 | XVFI | |
|---|---|---|
| 1 | 1 | |
| 976 | 260 | |
| 2.8% | - | |
| 0.0 | 0.0 | |
| almost 2 years ago | over 1 year ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | - |
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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.
XVFI
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[D] Has anyone compared XVFI's interpolation quality with RIFE?
GitHub - JihyongOh/XVFI: Official repository of XVFI (accepted in ICCV2021, Oral)
What are some alternatives?
pix2pixHD - Synthesizing and manipulating 2048x1024 images with conditional GANs
AnimeInterp - The code for CVPR21 paper "Deep Animation Video Interpolation in the Wild"
Pix2Vox - The official implementation of "Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images". (Xie et al., ICCV 2019)
frame-interpolation - FILM: Frame Interpolation for Large Motion, In ECCV 2022.
pi-GAN-pytorch - Implementation of π-GAN, for 3d-aware image synthesis, in Pytorch
fashion-mnist - A MNIST-like fashion product database. Benchmark :point_down:
NAFNet - The state-of-the-art image restoration model without nonlinear activation functions.
Super-SloMo - PyTorch implementation of Super SloMo by Jiang et al.
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.
DIML - [ICCV 2021] Towards Interpretable Deep Metric Learning with Structural Matching
CAIN - Source code for AAAI 2020 paper "Channel Attention Is All You Need for Video Frame Interpolation"
AgentFormer - [ICCV 2021] Official PyTorch Implementation of "AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting".