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 1351–1375 of 3874 papers

TitleStatusHype
Learning Series-Parallel Lookup Tables for Efficient Image Super-ResolutionCode0
Learning of Patch-Based Smooth-Plus-Sparse Models for Image ReconstructionCode0
Evaluating Robustness of Deep Image Super-Resolution against Adversarial AttacksCode0
Learning Multiple Probabilistic Degradation Generators for Unsupervised Real World Image Super ResolutionCode0
Light Field Super-resolution via Attention-Guided Fusion of Hybrid LensesCode0
Learning Likelihoods with Conditional Normalizing FlowsCode0
Maintaining Natural Image Statistics with the Contextual LossCode0
Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid NetworksCode0
Regularization by Neural Style Transfer for MRI Field-Transfer Reconstruction with Limited DataCode0
Arbitrary Scale Super-Resolution for Brain MRI ImagesCode0
SR+Codec: a Benchmark of Super-Resolution for Video Compression Bitrate ReductionCode0
Learning Descriptor Networks for 3D Shape Synthesis and AnalysisCode0
Learning a Single Convolutional Super-Resolution Network for Multiple DegradationsCode0
Learning a No-Reference Quality Metric for Single-Image Super-ResolutionCode0
Learning Accurate and Enriched Features for Stereo Image Super-ResolutionCode0
Ensemble Super-Resolution with A Reference DatasetCode0
LCSCNet: Linear Compressing Based Skip-Connecting Network for Image Super-ResolutionCode0
LD-GAN: Low-Dimensional Generative Adversarial Network for Spectral Image Generation with Variance RegularizationCode0
LatticeNet: Towards Lightweight Image Super-resolution with Lattice BlockCode0
Component Attention Guided Face Super-Resolution Network: CAGFaceCode0
Enhancing Super-Resolution Networks through Realistic Thick-Slice CT SimulationCode0
Latent Diffusion, Implicit Amplification: Efficient Continuous-Scale Super-Resolution for Remote Sensing ImagesCode0
Learned Block Iterative Shrinkage Thresholding Algorithm for Photothermal Super Resolution ImagingCode0
3DSRnet: Video Super-resolution using 3D Convolutional Neural NetworksCode0
Laplacian Pyramid-like AutoencoderCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified