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 2451–2475 of 3874 papers

TitleStatusHype
Rich Feature Distillation with Feature Affinity Module for Efficient Image Dehazing—0
RingCNN: Exploiting Algebraically-Sparse Ring Tensors for Energy-Efficient CNN-Based Computational Imaging—0
Robust Emotion Recognition from Low Quality and Low Bit Rate Video: A Deep Learning Approach—0
Robust Image Filtering Using Joint Static and Dynamic Guidance—0
Robust image reconstruction from multi-view measurements—0
Robust Multi-Image Based Blind Face Hallucination—0
Robust Online Video Super-Resolution Using an Efficient Alternating Projections Scheme—0
Robust PCA Unrolling Network for Super-resolution Vessel Extraction in X-ray Coronary Angiography—0
Robust Regression via Deep Negative Correlation Learning—0
Robust Single Image Super-Resolution via Deep Networks With Sparse Prior—0
Robust Spectral Compressed Sensing via Structured Matrix Completion—0
Robust Super-Resolution GAN, with Manifold-based and Perception Loss—0
Super-Resolution of Real-World Faces—0
Robust Unpaired Single Image Super-Resolution of Faces—0
Robust Video Super-Resolution With Learned Temporal Dynamics—0
Rolling Shutter Super-Resolution—0
Rotationally Equivariant Super-Resolution of Velocity Fields in Two-Dimensional Fluids Using Convolutional Neural Networks—0
RR-DnCNN v2.0: Enhanced Restoration-Reconstruction Deep Neural Network for Down-Sampling Based Video Coding—0
RRSR:Reciprocal Reference-based Image Super-Resolution with Progressive Feature Alignment and Selection—0
RSDiff: Remote Sensing Image Generation from Text Using Diffusion Model—0
RTSR: A Real-Time Super-Resolution Model for AV1 Compressed Content—0
S2Gaussian: Sparse-View Super-Resolution 3D Gaussian Splatting—0
S3RP: Self-Supervised Super-Resolution and Prediction for Advection-Diffusion Process—0
SAINT: Spatially Aware Interpolation NeTwork for Medical Slice Synthesis—0
Sampling Based Scene-Space Video Processing—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified