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 3201–3225 of 3874 papers

TitleStatusHype
Deeply Matting-based Dual Generative Adversarial Network for Image and Document Label Supervision—0
Multi-FAN: Multi-Spectral Mosaic Super-Resolution Via Multi-Scale Feature Aggregation Network—0
TextSR: Content-Aware Text Super-Resolution Guided by RecognitionCode1
Deep Learning for Low-Field to High-Field MR: Image Quality Transfer with Probabilistic Decimation Simulator—0
Phase Retrieval using Untrained Neural Network Priors—0
Blind Super-Resolution Kernel Estimation using an Internal-GANCode0
Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise ModulationsCode0
Edge-Informed Single Image Super-ResolutionCode0
Deep MR Brain Image Super-Resolution Using Spatio-Structural Priors—0
JSI-GAN: GAN-Based Joint Super-Resolution and Inverse Tone-Mapping with Pixel-Wise Task-Specific Filters for UHD HDR VideoCode0
Deep Super-Resolution Network for Single Image Super-Resolution with Realistic Degradations—0
LCSCNet: Linear Compressing Based Skip-Connecting Network for Image Super-ResolutionCode0
Supervised Learning Based Super-Resolution DoA Estimation Utilizing Antenna Array Extrapolation—0
Robust Online Video Super-Resolution Using an Efficient Alternating Projections Scheme—0
Virtual Thin Slice: 3D Conditional GAN-based Super-resolution for CT Slice Interval—0
Self-supervised Recurrent Neural Network for 4D Abdominal and In-utero MR Imaging—0
Robust Regression via Deep Negative Correlation Learning—0
Learning Filter Basis for Convolutional Neural Network CompressionCode1
DRFN: Deep Recurrent Fusion Network for Single-Image Super-Resolution with Large Factors—0
Progressive Face Super-Resolution via Attention to Facial LandmarkCode0
MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors—0
SROBB: Targeted Perceptual Loss for Single Image Super-Resolution—0
Image Formation Model Guided Deep Image Super-ResolutionCode0
RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-ResolutionCode0
Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement—0
Show:102550
← PrevPage 129 of 155Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified