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 931–940 of 3874 papers

TitleStatusHype
Make-A-Video: Text-to-Video Generation without Text-Video DataCode1
Learning Deep Interleaved Networks with Asymmetric Co-Attention for Image RestorationCode1
Learning Degradation Representations for Image DeblurringCode1
Learning Detail-Structure Alternative Optimization for Blind Super-ResolutionCode1
MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-ResolutionCode1
2-Step Sparse-View CT Reconstruction with a Domain-Specific Perceptual NetworkCode1
mdctGAN: Taming transformer-based GAN for speech super-resolution with Modified DCT spectraCode1
Degradation Oriented and Regularized Network for Blind Depth Super-ResolutionCode1
DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution ModelsCode1
An End-to-end Framework For Low-Resolution Remote Sensing Semantic SegmentationCode1
Show:102550
← PrevPage 94 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified