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 781–790 of 3874 papers

TitleStatusHype
A Two-Stage Attentive Network for Single Image Super-ResolutionCode1
Distribution-Flexible Subset Quantization for Post-Quantizing Super-Resolution NetworksCode1
Decoupled Data Consistency with Diffusion Purification for Image RestorationCode1
Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image AttenuationCode1
Burst Super-Resolution with Diffusion Models for Improving Perceptual QualityCode1
Deep Posterior Distribution-based Embedding for Hyperspectral Image Super-resolutionCode1
MaRINeR: Enhancing Novel Views by Matching Rendered Images with Nearby ReferencesCode1
DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable DiffusionCode1
MAT: Multi-Range Attention Transformer for Efficient Image Super-ResolutionCode1
Burstormer: Burst Image Restoration and Enhancement TransformerCode1
Show:102550
← PrevPage 79 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified