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

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Showing 1451–1500 of 3874 papers

TitleStatusHype
LAP: a Linearize and Project Method for Solving Inverse Problems with Coupled VariablesCode0
Laplacian Pyramid-like AutoencoderCode0
Kernel-aware Burst Blind Super-ResolutionCode0
ELSR: Extreme Low-Power Super Resolution Network For Mobile DevicesCode0
Kernel Modeling Super-Resolution on Real Low-Resolution ImagesCode0
JSI-GAN: GAN-Based Joint Super-Resolution and Inverse Tone-Mapping with Pixel-Wise Task-Specific Filters for UHD HDR VideoCode0
Adversarial Feedback LoopCode0
LAR-SR: A Local Autoregressive Model for Image Super-ResolutionCode0
Joint Maximum Purity Forest with Application to Image Super-ResolutionCode0
Efficient Deep Neural Network for Photo-realistic Image Super-ResolutionCode0
Joint Reconstruction and Spatial Super-Resolution of Hyper-Spectral CTIS Images via Multi-Scale RefinementCode0
AnyTSR: Any-Scale Thermal Super-Resolution for UAVCode0
Joint Super-Resolution and Alignment of Tiny FacesCode0
Joint Super-Resolution and Inverse Tone-Mapping: A Feature Decomposition Aggregation Network and A New BenchmarkCode0
IterInv: Iterative Inversion for Pixel-Level T2I ModelsCode0
City Scene Super-Resolution via Geometric Error MinimizationCode0
CISRNet: Compressed Image Super-Resolution NetworkCode0
3D Appearance Super-Resolution with Deep LearningCode0
Joint High Dynamic Range Imaging and Super-Resolution from a Single ImageCode0
Latent Diffusion, Implicit Amplification: Efficient Continuous-Scale Super-Resolution for Remote Sensing ImagesCode0
Efficient Single Image Super Resolution using Enhanced Learned Group ConvolutionsCode0
Efficient Residual Dense Block Search for Image Super-ResolutionCode0
Cine cardiac MRI reconstruction using a convolutional recurrent network with refinementCode0
Inverse Problems with Diffusion Models: A MAP Estimation PerspectiveCode0
IntraTomo: Self-Supervised Learning-Based Tomography via Sinogram Synthesis and PredictionCode0
Multi Scale Identity-Preserving Image-to-Image Translation Network for Low-Resolution Face RecognitionCode0
Efficient multi-class fetal brain segmentation in high resolution MRI reconstructions with noisy labelsCode0
Efficient Meta-Tuning for Content-aware Neural Video DeliveryCode0
Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational ApproachCode0
Advancing Super-Resolution in Neural Radiance Fields via Variational Diffusion StrategiesCode0
Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student LearningCode0
Efficient Light Field Reconstruction via Spatio-Angular Dense NetworkCode0
Efficient Integer-Arithmetic-Only Convolutional Neural NetworksCode0
Efficient Image Super-Resolution with Feature Interaction Weighted Hybrid NetworkCode0
FS-NCSR: Increasing Diversity of the Super-Resolution Space via Frequency Separation and Noise-Conditioned Normalizing FlowCode0
FSRNet: End-to-End Learning Face Super-Resolution with Facial PriorsCode0
A Novel End-To-End Network for Reconstruction of Non-Regularly Sampled Image Data Using Locally Fully Connected LayersCode0
Improved Pothole Detection Using YOLOv7 and ESRGANCode0
Improving Super-Resolution Methods via Incremental Residual LearningCode0
Implicit Image-to-Image Schrodinger Bridge for Image RestorationCode0
Efficient Event Stream Super-Resolution with Recursive Multi-Branch FusionCode0
Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate DataCode0
cGANs with Projection DiscriminatorCode0
Is Autoencoder Truly Applicable for 3D CT Super-Resolution?Code0
CFSNet: Toward a Controllable Feature Space for Image RestorationCode0
Image Super-Resolution via RL-CSC: When Residual Learning Meets Convolutional Sparse CodingCode0
Efficient and Accurate MRI Super-Resolution using a Generative Adversarial Network and 3D Multi-Level Densely Connected NetworkCode0
An Operator Learning Framework for Spatiotemporal Super-resolution of Scientific SimulationsCode0
Image Super-resolution via Feature-augmented Random ForestCode0
Image Super-Resolution via Deep Recursive Residual NetworkCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified