Topic: swinir Goto Github
Some thing interesting about swinir
Some thing interesting about swinir
swinir,Analysis resources for the Inter IIT Tech Meet 11.0 problem statement by ISRO: The Chandrayaan Moon Mapping Challenge
Organization: astroclubiitk
swinir,A repository of models trained by me!
User: bubblemint864
swinir,Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR
User: cszn
Home Page: https://cszn.github.io/
swinir,A High Quality (HD / 2K / 4K) Image Generation Using Stable Diffusion and Real-ESR / SwinIR /GFPGAN
User: hemantkarya
Home Page: https://www.instagram.com/iamhemantindia
swinir,🌊 A Human-in-the-Loop workflow for creating HD images from text
Organization: jina-ai
Home Page: grpcs://dalle-flow.dev.jina.ai
swinir,Video Frame Interpolation & Super Resolution using NVIDIA's TensorRT & Tencent's NCNN inference, beautifully crafted and packaged into a single app
User: mafiosnik777
Home Page: https://dsc.gg/enhancr
swinir,[ECCV] Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration. Advances in Image Manipulation (AIM) workshop ECCV 2022. Try it out! over 3.3M runs https://replicate.com/mv-lab/swin2sr
User: mv-lab
Home Page: https://arxiv.org/abs/2209.11345
swinir,Proposed model on Individual Study (Lab. Intern)
User: novwaul
swinir,My VitePress website I made to visually compare the output I created with over 600 different AI upscaling models. Running under https://phhofm.github.io/upscale/
User: phhofm
Home Page: https://phhofm.github.io/upscale/
swinir,A multistage text to image framework. Built from a inference-reduced set of min-dalle, glid-3-xl, and SwinIR.
User: rypo
swinir,WindSR Dataset contains more than 22,000 pairs of HR/LR wind speed images, which are processed using the NASA's GEOS-5 Nature Run dataset. This dataset is useful for studying super-resolution for data collected using satellites rather natural RGB images.
Organization: sekilab
swinir,Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.
Organization: xpixelgroup
Home Page: https://basicsr.readthedocs.io/en/latest/
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