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 3471–3480 of 3874 papers

TitleStatusHype
Towards Progressive Multi-Frequency Representation for Image WarpingCode0
ASDN: A Deep Convolutional Network for Arbitrary Scale Image Super-ResolutionCode0
Super-Resolution Surface Reconstruction from Few Low-Resolution SlicesCode0
CausalSR: Structural Causal Model-Driven Super-Resolution with Counterfactual InferenceCode0
Leveraging Segment Anything Model in Identifying Buildings within Refugee Camps (SAM4Refugee) from Satellite Imagery for Humanitarian OperationsCode0
Camera Lens Super-ResolutionCode0
PFT-SSR: Parallax Fusion Transformer for Stereo Image Super-ResolutionCode0
Single Image Super-Resolution with Dilated Convolution based Multi-Scale Information Learning Inception ModuleCode0
C2PD: Continuity-Constrained Pixelwise Deformation for Guided Depth Super-ResolutionCode0
Efficient and Accurate MRI Super-Resolution using a Generative Adversarial Network and 3D Multi-Level Densely Connected NetworkCode0
Show:102550
← PrevPage 348 of 388Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified