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Methods and Pretrained Models

Methods and pre-trained models used in 4KAgent are summarized as follows:

Task Method Method Repo Pretrained model from
Brightening CLAHE N/A N/A
Brightening Constant Shift (C = 40) N/A N/A
Brightening DiffPlugin https://github.com/yuhaoliu7456/Diff-Plugin https://github.com/yuhaoliu7456/Diff-Plugin/tree/main/pre-trained/lowlight
Brightening FourierDiff https://github.com/aipixel/fourierdiff https://openai-public.blob.core.windows.net/diffusion/jul-2021/256x256_diffusion_uncond.pt
Brightening Gamma Correction N/A N/A
Brightening MAXIM https://github.com/google-research/maxim https://console.cloud.google.com/storage/browser/gresearch/maxim/ckpt/Enhancement/LOL;tab=objects?prefix=&forceOnObjectsSortingFiltering=false
Defocus Deblurring ConvIR https://github.com/c-yn/ConvIR https://drive.google.com/drive/folders/1_5fO2p5xoWO5cUEVoXJ7x3Uhg1AP18FQ -> dpdd-large.pkl
Defocus Deblurring DiffPlugin https://github.com/yuhaoliu7456/Diff-Plugin https://github.com/yuhaoliu7456/Diff-Plugin/tree/main/pre-trained/deblur
Defocus Deblurring DRBNet https://github.com/lingyanruan/DRBNet https://drive.google.com/file/d/1vGlmev9LdagttXE_nN1gZGVstVTRVQHT/view?usp=sharing -> single_image_defocus_deblurring.pth
Defocus Deblurring IFAN https://github.com/codeslake/IFAN https://www.dropbox.com/s/qohrmpr9b1u0syi/checkpoints.zip?dl=1 -> IFAN_44.pytorch
Defocus Deblurring LaKDNet https://github.com/lingyanruan/LaKDNet https://lakdnet.mpi-inf.mpg.de/ -> train_on_dpdd_l.pth
Defocus Deblurring Restormer https://github.com/swz30/Restormer https://drive.google.com/drive/folders/1bRBG8DG_72AGA6-eRePvChIT5ZO4cwJ4 -> single_image_defocus_deblurring.pth
Motion Deblurring EVSSM https://github.com/kkkis/EVSSM https://drive.google.com/drive/folders/1_G0hf1KX_SAvyK41bdGm2q0q63B6wN40 -> net_g_GoPro.pth
Motion Deblurring LaKDNet https://github.com/lingyanruan/LaKDNet https://lakdnet.mpi-inf.mpg.de/ -> train_on_realr_l.pth
Motion Deblurring MAXIM https://github.com/google-research/maxim https://console.cloud.google.com/storage/browser/gresearch/maxim/ckpt/Deblurring/RealBlur_R;tab=objects?prefix=&forceOnObjectsSortingFiltering=false
Motion Deblurring MPRNet https://github.com/swz30/MPRNet https://drive.google.com/file/d/1QwQUVbk6YVOJViCsOKYNykCsdJSVGRtb/view
Motion Deblurring NAFNet https://github.com/megvii-research/NAFNet https://drive.google.com/file/d/1S0PVRbyTakYY9a82kujgZLbMihfNBLfC/view
Motion Deblurring Restormer https://github.com/swz30/Restormer https://drive.google.com/drive/folders/1czMyfRTQDX3j3ErByYeZ1PM4GVLbJeGk
Motion Deblurring X-Restormer https://github.com/Andrew0613/X-Restormer https://drive.google.com/drive/folders/1C8hEafMx8ivmujzk7l2c_bPhGRu6xBHX
Dehazing DehazeFormer https://github.com/IDKiro/DehazeFormer https://drive.google.com/drive/folders/1qnQil_7Dvy-ZdQUVYXt7pW0EFQkpK39B
Dehazing DiffPlugin https://github.com/yuhaoliu7456/Diff-Plugin https://github.com/yuhaoliu7456/Diff-Plugin/tree/main/pre-trained/dehaze
Dehazing MAXIM https://github.com/google-research/maxim https://console.cloud.google.com/storage/browser/gresearch/maxim/ckpt/Dehazing/SOTS-Outdoor;tab=objects?prefix=&forceOnObjectsSortingFiltering=false
Dehazing RIDCP https://github.com/RQ-Wu/RIDCP_dehazing https://pan.baidu.com/share/init?surl=ps9dPmerWyXlLxb6lkHihQ (pwd:huea)
Dehazing X-Restormer https://github.com/Andrew0613/X-Restormer https://drive.google.com/drive/folders/1_Cc2_3_P7hU4aTIWoa-lU3Ug70fS0oHd
Deraining DiffPlugin https://github.com/yuhaoliu7456/Diff-Plugin https://github.com/yuhaoliu7456/Diff-Plugin/tree/main/pre-trained/derain
Deraining MAXIM https://github.com/google-research/maxim https://console.cloud.google.com/storage/browser/gresearch/maxim/ckpt/Deraining/Rain13k;tab=objects?prefix=&forceOnObjectsSortingFiltering=false
Deraining MPRNet https://github.com/swz30/MPRNet https://drive.google.com/file/d/103WEJbcat7eTY6doXWeorAB1oMmMnM/view
Deraining Restormer https://github.com/swz30/Restormer https://drive.google.com/drive/folders/1ZEDDEW0UkqpWk-N4Li_JUoVGhGXCu_u
Deraining X-Restormer https://github.com/Andrew0613/X-Restormer https://drive.google.com/drive/folders/16eCJ7R1CDYhDLqS7KzFUZY_zD1uo2S
Denoising MAXIM https://github.com/google-research/maxim https://console.cloud.google.com/storage/browser/gresearch/maxim/ckpt/Denoising/SIDD;tab=objects?prefix=&forceOnObjectsSortingFiltering=false
Denoising MPRNet https://github.com/swz30/MPRNet https://drive.google.com/file/d/1LODPl9kYJmxuU98g9dRuRoanE5HyfCsRw/view
Denoising NAFNet https://github.com/megvii-research/NAFNet https://drive.google.com/file/d/14ff1hQZJqzMIkAntEpXoWJbU6aIWWR/view
Denoising Restormer https://github.com/swz30/Restormer https://drive.google.com/drive/folders/1Qswjny54ZRWa7cA4ap7exiXLBo4uF40 -> real_denoising.pth
Denoising X-Restormer https://github.com/Andrew0613/X-Restormer https://drive.google.com/drive/folders/1-vcU7JiJQNSewTbNCS2j9lIKOZ0W89
Denoising SwinIR (15) https://github.com/JingyunLiang/SwinIR https://github.com/JingyunLiang/SwinIR/releases/tag/v0.0 -> 005_colorDN_DFWB_s128w8_SwinIR-M_noise15.pth
Denoising SwinIR (50) https://github.com/JingyunLiang/SwinIR https://github.com/JingyunLiang/SwinIR/releases/tag/v0.0 -> 005_colorDN_DFWB_s128w8_SwinIR-M_noise50.pth
JPEG CAR FBANN (5) https://github.com/jiaxi-jiang/FBCNN https://github.com/jiaxi-jiang/FBCNN/releases/tag/v1.0 -> fbcnn_color.pth
JPEG CAR FBANN (90) https://github.com/jiaxi-jiang/FBCNN https://github.com/jiaxi-jiang/FBCNN/releases/tag/v1.0 -> fbcnn_color.pth
JPEG CAR FBANN (B) https://github.com/jiaxi-jiang/FBCNN https://github.com/jiaxi-jiang/FBCNN/releases/tag/v1.0 -> fbcnn_color.pth
JPEG CAR SwinIR https://github.com/JingyunLiang/SwinIR https://github.com/JingyunLiang/SwinIR/releases/tag/v0.0 -> 006_colorCAR_DFWB_s126w7_SwinIR-M_jpeg40.pth
Super-Resolution DiffBIR https://github.com/XPixelGroup/DiffBIR https://huggingface.co/xql007/diffbir-v2/resolve/main/v2.pt
Super-Resolution DRCT https://github.com/ning0531/DRCT https://drive.google.com/drive/folders/1J0JHdSfOePNh96ibgzMJAJPw31ug9z7U -> DRCT-L_X4.pth
Super-Resolution HAT-L https://github.com/XPixelGroup/HAT https://drive.google.com/drive/folders/1HpmReFoUqUnBAOQ7yoENuU3uf_m69w0 -> HAT-L_SRx4_ImageNet-pretrain.pth
Super-Resolution HAT-GAN https://github.com/XPixelGroup/HAT https://drive.google.com/drive/folders/1HpmReFoUqUnBAOQ7yoENuU3uf_m69w0 -> Real_HAT_GAN_sharper.pth
Super-Resolution HMA https://github.com/Korouoruw/HMA https://drive.google.com/drive/folders/13Bxt_BXtVWQ0crgL7lo6rYZAUY1v3zi -> HMA_SRx4_pretrain.pth
Super-Resolution OSEDiff https://github.com/cswry/OSEDiff https://github.com/cswry/OSEDiff/tree/main/prest/models
Super-Resolution PiSA-SR https://github.com/csslc/PiSA-SR https://drive.google.com/drive/folders/1eljWWMds9xJwseL2SEoJvXQBiFxWds
Super-Resolution SwinIR https://github.com/JingyunLiang/SwinIR https://github.com/JingyunLiang/SwinIR/releases/tag/v0.0 -> 003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_PSNR.pth
Super-Resolution SwinIR (Real-ISR) https://github.com/JingyunLiang/SwinIR https://github.com/JingyunLiang/SwinIR/releases/tag/v0.0 -> 003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth
Super-Resolution SwinFIR https://github.com/ZdAeng/SwinFIR https://drive.google.com/drive/folders/9dQAXbISB7zEy2UJK7AU1W6EJloK -> SwinFIR_SRx4.pth
Super-Resolution X-Restormer https://github.com/Andrew0613/X-Restormer https://drive.google.com/drive/folders/1GiK8cfRdcjAPPN3Qt6b7AKveBAH_AS
Face-Restoration GFPGAN https://github.com/TencentARC/GFPGAN https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth
Face-Restoration CodeFormer https://github.com/sczhou/CodeFormer https://drive.google.com/drive/folders/1S_wQNBNYjbHFtD95qb4YMv6plfo5iuU6QS
Face-Restoration DiffFace https://github.com/zsyOAOA/DiffFace https://github.com/zsyOAOA/DiffFace/releases/tag/V1.0
Old Photo Restoration BOBL https://github.com/microsoft/Bringing-Old-Photos-Back-to-Life https://github.com/microsoft/Bringing-Old-Photos-Back-to-Life/releases/tag/v1.0
Human Preference Evaluation HPSv2 https://github.com/tgxs002/HPSv2 https://github.com/tgxs002/HPSv2/blob/master/hpsv2/src/open_clip/bpe_simple_vocab_16e6.txt.gz

We sincerely acknowledge these open-source codes and pre-trained models.