BJDD_CVPR21
SwinIR
| BJDD_CVPR21 | SwinIR | |
|---|---|---|
| 1 | 28 | |
| 63 | 4,091 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 2 years ago | about 1 month ago | |
| Python | Python | |
| - | Apache License 2.0 |
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BJDD_CVPR21
SwinIR
- A smooth and sharp image interpolation you probably haven't heard of
- Certain directories (e.g. SwinIR) are empty (version: Empire Media Science A1111 Web UI Installer)
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I used Real-ESRGAN to upscale my image, but if you zoom in you can see that “water particles” looks like some random lines and image overall looks cartoonish. Is there a way to fix it?
003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth
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Any luck changing the upscaler? They seem to be hard coded
I was trying to get a new upscaler working, as someone pointed me to one that did a good job of preserving and creating new details: https://github.com/JingyunLiang/SwinIR
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Spatial-temporal denoising
SwinIR: https://github.com/JingyunLiang/SwinIR
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A Monster Hunter: World Virtual Photography Tutorial - YouTube
Upscalers that I use SwinIR https://github.com/JingyunLiang/SwinIR https://github.com/AUTOMATIC1111/stable-diffusion-webui (Use 'extras' tab for the upscaler function) Topaz Gigapixel AI https://www.topazlabs.com/gigapixel-ai
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what are the alternatives to letsenhance.io?
You could try out chaiNNer, it is a free local/offline application. There are a lot of (upscaling) models which you can download an use with it. You can for example try out SwinIR-L (link will start a model download) or any other model you like depending on your input images.
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[R] Swin transformer while using a rectangular attention window
the relative attention bias can be made non-square in the original implementation, there is a parameter window_size, at 7, that is forced to (7,7) directly, but you can change it easily. https://github.com/JingyunLiang/SwinIR/blob/main/models/network_swinir.py
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Robot dance animation with Robo-Diffusion (1024x576)
Use SwinIR medium model to upscale by 2 times. This will result in a video of 2048x1152.
- Help Need to get my VQGAN images to 10000 x 10000
What are some alternatives?
nind-denoise - Image denoising using the Natural Image Noise Dataset
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
virtex - [CVPR 2021] VirTex: Learning Visual Representations from Textual Annotations
image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Real-ESRGAN-ncnn-vulkan - NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
Ne2Ne-Image-Denoising - Deep Unsupervised Image Denoising, based on Neighbour2Neighbour training
chaiNNer - A node-based image processing GUI aimed at making chaining image processing tasks easy and customizable. Born as an AI upscaling application, chaiNNer has grown into an extremely flexible and powerful programmatic image processing application.
MPRNet - [CVPR 2021] Multi-Stage Progressive Image Restoration. SOTA results for Image deblurring, deraining, and denoising.
LaTeX-OCR - pix2tex: Using a ViT to convert images of equations into LaTeX code.
CogView - Text-to-Image generation. The repo for NeurIPS 2021 paper "CogView: Mastering Text-to-Image Generation via Transformers".
Cream - This is a collection of our NAS and Vision Transformer work. [Moved to: https://github.com/microsoft/AutoML]
Restormer - [CVPR 2022--Oral] Restormer: Efficient Transformer for High-Resolution Image Restoration. SOTA for motion deblurring, image deraining, denoising (Gaussian/real data), and defocus deblurring.