DE-GAN
Document Image Enhancement with GANs - TPAMI journal (by dali92002)
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. (by York-SDCNLab)
| DE-GAN | Ghost-DeblurGAN | |
|---|---|---|
| 1 | 1 | |
| 151 | 35 | |
| - | - | |
| 0.0 | 3.4 | |
| about 1 year ago | 8 months ago | |
| Python | Python | |
| GNU General Public License v3.0 only | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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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.
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.
DE-GAN
Posts with mentions or reviews of DE-GAN.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-05-04.
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Is there an AI that can un-grain text?
Looks like you could try DE-GAN https://github.com/dali92002/DE-GAN
Ghost-DeblurGAN
Posts with mentions or reviews of Ghost-DeblurGAN.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Apriltag pose detection on curved surface
You could try some sort of Image restoration GAN to produce a modified output of the input image (which lies on the curved surface). I have conducted research on GANs for deblurring Fiducial markers, and simply put, the Network takes a blurred image containing fiducial markers and outputs a ‘deblurred image’ whose fiducial markers can be more easily detected. However, keep in mind that the GANs can perform a wide variety of operations on an input Image (other than just deblurring), hence, they are called Image restoration networks in general. What you could give a shot is, create a pipeline where the captured image goes into the GAN, then the output is fed to the Apriltag detector. Here is the link to our GitHub if you need a starter: https://github.com/York-SDCNLab/Ghost-DeblurGAN, and some of my other suggestions are NAFNet and HINet.
What are some alternatives?
When comparing DE-GAN and Ghost-DeblurGAN you can also consider the following projects:
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
DeblurGANv2 - [ICCV 2019] "DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better" by Orest Kupyn, Tetiana Martyniuk, Junru Wu, Zhangyang Wang
pix2pixHD - Synthesizing and manipulating 2048x1024 images with conditional GANs
StyleGAN.pytorch - A PyTorch implementation for StyleGAN with full features.
pytorch-fid - Compute FID scores with PyTorch.
ALAE - [CVPR2020] Adversarial Latent Autoencoders
tapnet - Tracking Any Point (TAP)
TextZoom - A super-resolution dataset of paired LR-HR scene text images