画像超解像度
画像のスーパーレゾリューションは、低解像度の画像を高解像度に拡大する機械学習タスクで、通常は4倍以上の拡大率を使用します。この技術は、画像の内容と詳細をできるだけ保ちつつ、画像品質の大幅な向上、視覚効果の強化、コンピュータビジョンアルゴリズムの精度向上を実現し、さまざまな場面での応用が可能です。
Set14 - 4x upscaling
HAT-L
BSD100 - 4x upscaling
Config (e)
Urban100 - 4x upscaling
HMA†
Manga109 - 4x upscaling
SwinIR
Set5 - 2x upscaling
HAT-L
Set14 - 2x upscaling
DRCT-L
Set5 - 3x upscaling
HMA†
BSD100 - 2x upscaling
WaveMixSR-V2
Urban100 - 2x upscaling
Set14 - 3x upscaling
DRLN+
Urban100 - 3x upscaling
DRLN+
BSD100 - 3x upscaling
HAT
DIV2K val - 4x upscaling
EDSR
Manga109 - 2x upscaling
DRCT-L
Manga109 - 3x upscaling
DRLN+
FFHQ 256 x 256 - 4x upscaling
HiFaceGAN
Set5 - 4x upscaling
FFHQ 1024 x 1024 - 4x upscaling
IXI
EDSR+MMHCA
FFHQ 512 x 512 - 4x upscaling
HiFaceGAN
Set5 - 8x upscaling
DBPN-RES-MR64-3
Set14 - 8x upscaling
DBPN-RES-MR64-3
VggFace2 - 8x upscaling
Full-GWAInet
WebFace - 8x upscaling
GFRNet
BSD100 - 8x upscaling
DRLN+
CelebA
ImageNet
DAVI
Manga109 - 8x upscaling
DBPN-RES-MR64-3
Urban100 - 8x upscaling
DRLN+
DIV8K val - 16x upscaling
Ours w/o cycle-loss
General100 - 4x upscaling
SROOE
PIRM-test
RankSRGAN
2x upscaling
3x upscaling
4x upscaling
B100 - 2x upscaling
B100 - 3x upscaling
ML-CrAIST
B100 - 4x upscaling
BSDS100 - 2x upscaling
DBPN-RES-MR64-3
CelebA-HQ 128x128
IDM
CUFED5 - 4x upscaling
DIV2K val - 8x upscaling
General100 - 8x upscaling
FxSR-PD t=0.8
Sun80 - 4x upscaling
SRNTT-l2
BSD100 - 16x upscaling
ABPN
BSD200 - 2x upscaling
BSDS100 - 4x upscaling
DBPN-RES-MR64-3
BSDS100 - 8x upscaling
DBPN-RES-MR64-3
Celeb-HQ 4x upscaling
Edge-informed SR
Chikusei Dataset
DIP-HyperKite (ours)
DIV2K val - 16x upscaling
ABPN
DIV8K test - 16x upscaling
RFB-ESRGAN
EPFL NIR-VIS
RAMS (ours)
General-100 - 4x upscaling
KITTI 2012 - 2x upscaling
KITTI 2012 - 4x upscaling
PASSRnet
KITTI 2015 - 2x upscaling
KITTI 2015 - 4x upscaling
PASSRnet
Manga109 - 16x upscaling
ABPN
Middlebury - 2x upscaling
Middlebury - 4x upscaling
PASSRnet
Set14
ATD
Set5 - 5x upscaling
Set5 - 6x upscaling
ShipSpotting
StableShip
Urban100 - 16x upscaling
ABPN
USR-248 - 4x upscaling
SRDRM-GAN
WLFW
ArcFace (0.4)