Image To Image Translation
Image-to-Image Translation is a task in the field of computer vision and machine learning that aims to learn the mapping relationship between input images and output images to achieve specific goals, such as style transfer, data augmentation, or image restoration. By constructing complex models, this task can effectively transform the visual attributes of images, enhancing the diversity and flexibility of image processing, and has a wide range of application values.
2017_test set
ADE-Indoor Labels-to-Photo
SB-GAN
ADE20K Labels-to-Photos
INADE
ADE20K-Outdoor Labels-to-Photos
DP-GAN
Aerial-to-Map
cGAN
AFHQ
StarGAN v2
AFHQ (Cat to Dog)
AFHQ (Wild to Dog)
EGSDE
anime-to-selfie
FQ-GAN
Apples and Oranges
BCI
pyramidpix2pix
BRATS
cat2dog
U-GAT-IT
CelebA-HQ
StarGAN v2
Cityscapes Labels-to-Photo
OASIS
Cityscapes Photo-to-Labels
pix2pix
Cityscapes-to-Foggy Cityscapes
MIC
COCO-Stuff Labels-to-Photos
PITI
Deep-Fashion
INADE
dog2cat
FLIR
GTAV-to-Cityscapes Labels
ResNet101 65.1
horse2zebra
CycleGANAS
IXI
ResViT
KITTI Object Tracking Evaluation 2012
SRNet
LLVIP
Object Transfiguration (sheep-to-giraffe)
InstaGAN
photo2portrait
U-GAT-IT
photo2vangogh
U-GAT-IT
portrait2photo
RaFD
StarGAN
selfie-to-anime
FQ-GAN
selfie2anime
GNR
SYNTHIA Fall-to-Winter
CyCADA
SYNTHIA-to-Cityscapes
vangogh2photo
U-GAT-IT
Zebra and Horses
Shared discriminator GAN
zebra2horse
CycleGAN