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 331–340 of 3874 papers

TitleStatusHype
IGAF: Incremental Guided Attention Fusion for Depth Super-Resolution—0
Compressed Domain Prior-Guided Video Super-Resolution for Cloud Gaming Content—0
Transformer-Driven Inverse Problem Transform for Fast Blind Hyperspectral Image Dehazing—0
Embedding Similarity Guided License Plate Super Resolution—0
Spk2SRImgNet: Super-Resolve Dynamic Scene from Spike Stream via Motion Aligned Collaborative Filtering—0
Efficient Video Super-Resolution for Real-time Rendering with Decoupled G-buffer Guidance—0
ADD: Attribution-Driven Data Augmentation Framework for Boosting Image Super-Resolution—0
S2Gaussian: Sparse-View Super-Resolution 3D Gaussian Splatting—0
Deterministic Image-to-Image Translation via Denoising Brownian Bridge Models with Dual ApproximatorsCode1
DORNet: A Degradation Oriented and Regularized Network for Blind Depth Super-Resolution—0
Show:102550
← PrevPage 34 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified