Image Super Resolution On Set5 3X Upscaling

PSNR

Résultats

Résultats de performance de divers modèles sur ce benchmark

Tableau comparatif

Nom du modèle	PSNR
lightweight-image-super-resolution-with-1	34.36
feedback-network-for-image-super-resolution	34.70
hmanet-hybrid-multi-axis-aggregation-network	35.35
drct-saving-image-super-resolution-away-from	35.18
lightweight-feature-fusion-network-for-single	34.04
lcscnet-linear-compressing-based-skip	33.99
learning-deep-cnn-denoiser-prior-for-image	31.26
image-super-resolution-with-cross-scale-non	34.74
hierarchical-information-flow-for-generalized	35.2
ml-craist-multi-scale-low-high-frequency	34.7
modulating-image-restoration-with-continual	34.34
feature-based-adaptive-contrastive	34.729
swinfir-revisiting-the-swinir-with-fast	35.21
drct-saving-image-super-resolution-away-from	35.32
beyond-a-gaussian-denoiser-residual-learning	33.75
swinfir-revisiting-the-swinir-with-fast	35.15
progressive-multi-scale-residual-network-for	34.65
activating-more-pixels-in-image-super	35.16
image-restoration-using-convolutional-auto	33.82
multi-level-wavelet-cnn-for-image-restoration	34.17
densely-residual-laplacian-super-resolution	34.86
ml-craist-multi-scale-low-high-frequency	34.58
channel-partitioned-windowed-attention-and	35.16
local-texture-estimator-for-implicit	34.89
one-size-fits-all-hypernetwork-for-tunable	29.77
channel-partitioned-windowed-attention-and	35.19
image-restoration-using-deep-regulated	33.43
single-image-super-resolution-via-a-holistic	34.85
a-framework-for-real-time-object-detection	34.69
activating-more-pixels-in-image-super	35.28
on-efficient-transformer-and-image-pre	35.13
neural-nearest-neighbors-networks	33.84