HyperAI
Startseite
Neuigkeiten
Neueste Forschungsarbeiten
Tutorials
Datensätze
Wiki
SOTA
LLM-Modelle
GPU-Rangliste
Veranstaltungen
Suche
Über
Deutsch
System
HyperAI
Toggle sidebar
Seite durchsuchen…
⌘
K
Anmelden
Anmelden
Startseite
SOTA
Image Super Resolution
Image Super Resolution On Set14 2X Upscaling
Image Super Resolution On Set14 2X Upscaling
Metriken
PSNR
SSIM
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
PSNR
SSIM
Paper Title
Repository
DRCT-L
35.36
0.9302
DRCT: Saving Image Super-resolution away from Information Bottleneck
ML-CrAIST-Li
33.64
0.9213
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer
CPAT
34.91
0.9277
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution
-
SwinOIR
33.97
0.922
Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection Strategy
MWCNN
33.7
-
Multi-level Wavelet-CNN for Image Restoration
MaIR
34.75
0.9268
MaIR: A Locality- and Continuity-Preserving Mamba for Image Restoration
-
CSRCNN
34.34
0.9240
Cascade Convolutional Neural Network for Image Super-Resolution
-
HAT-L
35.29
0.9293
Activating More Pixels in Image Super-Resolution Transformer
HAT
35.13
0.9282
Activating More Pixels in Image Super-Resolution Transformer
CPAT+
34.97
0.9280
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution
-
DRCT
34.96
0.9287
DRCT: Saving Image Super-resolution away from Information Bottleneck
DRLN+
34.43
0.9247
Densely Residual Laplacian Super-Resolution
HBPN
33.78
0.921
Hierarchical Back Projection Network for Image Super-Resolution
DRCN [[Kim et al.2016b]]
33.04
-
Deeply-Recursive Convolutional Network for Image Super-Resolution
DnCNN-3
33.03
-
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
DBPN-RES-MR64-3
34.09
0.921
Deep Back-Projection Networks for Single Image Super-resolution
Deep CNN Denoiser
30.79
-
Learning Deep CNN Denoiser Prior for Image Restoration
HAT_FIR
35.17
-
SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
ML-CrAIST
33.77
0.922
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer
HAN+
34.24
0.9224
Single Image Super-Resolution via a Holistic Attention Network
0 of 35 row(s) selected.
Previous
Next