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 51–60 of 3874 papers

TitleStatusHype
PP-MSVSR: Multi-Stage Video Super-ResolutionCode3
SwinIR: Image Restoration Using Swin TransformerCode3
BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and AlignmentCode3
BasicVSR: The Search for Essential Components in Video Super-Resolution and BeyondCode3
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative ModelsCode3
ESRGAN: Enhanced Super-Resolution Generative Adversarial NetworksCode3
Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature TransformCode3
EAMamba: Efficient All-Around Vision State Space Model for Image RestorationCode2
DOVE: Efficient One-Step Diffusion Model for Real-World Video Super-ResolutionCode2
VisualQuality-R1: Reasoning-Induced Image Quality Assessment via Reinforcement Learning to RankCode2
Show:102550
← PrevPage 6 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified