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 1751–1800 of 3874 papers

TitleStatusHype
A full-resolution training framework for Sentinel-2 image fusion—0
Benchmarking Super-Resolution Algorithms on Real Data—0
Image inpainting for corrupted images by using the semi-super resolution GAN—0
Image Inpainting for High-Resolution Textures using CNN Texture Synthesis—0
Image Neural Field Diffusion Models—0
Imagen Video: High Definition Video Generation with Diffusion Models—0
ImagePairs: Realistic Super Resolution Dataset via Beam Splitter Camera Rig—0
Image Processing GNN: Breaking Rigidity in Super-Resolution—0
Convolutional Sparse Coding for Image Super-Resolution—0
Joint Face Super-Resolution and Deblurring Using a Generative Adversarial Network—0
FB-HyDON: Parameter-Efficient Physics-Informed Operator Learning of Complex PDEs via Hypernetwork and Finite Basis Domain Decomposition—0
Image Reconstruction of Multi Branch Feature Multiplexing Fusion Network with Mixed Multi-layer Attention—0
Deep machine learning-assisted multiphoton microscopy to reduce light exposure and expedite imaging—0
Image Resolution Enhancement by Using Interpolation Followed by Iterative Back Projection—0
Image Restoration by Deep Projected GSURE—0
A Single Video Super-Resolution GAN for Multiple Downsampling Operators based on Pseudo-Inverse Image Formation Models—0
Joint Flow And Feature Refinement Using Attention For Video Restoration—0
Fast Sublinear Sparse Representation using Shallow Tree Matching Pursuit—0
FastSR-NeRF: Improving NeRF Efficiency on Consumer Devices with A Simple Super-Resolution Pipeline—0
Image Restoration using Autoencoding Priors—0
Fast Spatio-Temporal Residual Network for Video Super-Resolution—0
Fast single image super-resolution based on sigmoid transformation—0
Convolutional neural network based on sparse graph attention mechanism for MRI super-resolution—0
Joint Generative Learning and Super-Resolution For Real-World Camera-Screen Degradation—0
Fast Single Image Super-Resolution—0
Image Super-Resolution Based on Sparsity Prior via Smoothed l_0 Norm—0
Convolutional Low-Resolution Fine-Grained Classification—0
Deep Networks for Image and Video Super-Resolution—0
A Single-Frame and Multi-Frame Cascaded Image Super-Resolution Method—0
Fast Randomized-MUSIC for mm-Wave Massive MIMO Radars—0
Image Super-resolution Reconstruction Network based on Enhanced Swin Transformer via Alternating Aggregation of Local-Global Features—0
Image Super-Resolution Using Attention Based DenseNet with Residual Deconvolution—0
Fast Online Video Super-Resolution with Deformable Attention Pyramid—0
Convolutional Bipartite Attractor Networks—0
A Comprehensive Survey of Transformers for Computer Vision—0
Image Super-Resolution using Explicit Perceptual Loss—0
Convergent plug-and-play with proximal denoiser and unconstrained regularization parameter—0
Image Super-Resolution Using T-Tetromino Pixels—0
A Simple Plugin for Transforming Images to Arbitrary Scales—0
Fast Neural Architecture Search for Lightweight Dense Prediction Networks—0
Controlling Neural Networks via Energy Dissipation—0
A Frequency Domain Neural Network for Fast Image Super-resolution—0
Joint Face Hallucination and Deblurring via Structure Generation and Detail Enhancement—0
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation—0
Fast Image Super-Resolution Based on In-Place Example Regression—0
Contrastive Learning for Climate Model Bias Correction and Super-Resolution—0
A Simple Framework to Leverage State-Of-The-Art Single-Image Super-Resolution Methods to Restore Light Fields—0
Fast Image Deconvolution using Hyper-Laplacian Priors—0
Joint Demosaicing and Super-Resolution (JDSR): Network Design and Perceptual Optimization—0
Contrast: A Hybrid Architecture of Transformers and State Space Models for Low-Level Vision—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified