SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1031–1040 of 3874 papers

TitleStatusHype
DREAM: Diffusion Rectification and Estimation-Adaptive ModelsCode1
Discovering Distinctive "Semantics" in Super-Resolution NetworksCode1
Accurate Image Restoration with Attention Retractable TransformerCode1
Waving Goodbye to Low-Res: A Diffusion-Wavelet Approach for Image Super-ResolutionCode1
Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-ResolutionCode1
NEMO: enabling neural-enhanced video streaming on commodity mobile devicesCode1
Neural Sparse Representation for Image RestorationCode1
Distribution-Flexible Subset Quantization for Post-Quantizing Super-Resolution NetworksCode1
Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: ReportCode1
N-Gram in Swin Transformers for Efficient Lightweight Image Super-ResolutionCode1
Show:102550
← PrevPage 104 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified