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 1726–1750 of 3874 papers

TitleStatusHype
Hyperspectral Spatial Super-Resolution using Keystone Error—0
A Sinkhorn Regularized Adversarial Network for Image Guided DEM Super-resolution using Frequency Selective Hybrid Graph Transformer—0
3D Volumetric Super-Resolution in Radiology Using 3D RRDB-GAN—0
Involution and BSConv Multi-Depth Distillation Network for Lightweight Image Super-Resolution—0
Hyperspectral Super-Resolution via Interpretable Block-Term Tensor Modeling—0
A full-resolution training framework for Sentinel-2 image fusion—0
Hyperspectral Super-Resolution via Coupled Tensor Ring Factorization—0
Convolutional Sparse Coding for Image Super-Resolution—0
Strict Enforcement of Conservation Laws and Invertibility in CNN-Based Super Resolution for Scientific Datasets—0
HypervolGAN: An efficient approach for GAN with multi-objective training function—0
FB-HyDON: Parameter-Efficient Physics-Informed Operator Learning of Complex PDEs via Hypernetwork and Finite Basis Domain Decomposition—0
Deep Learning Framework for Infrastructure Maintenance: Crack Detection and High-Resolution Imaging of Infrastructure Surfaces—0
ICF-SRSR: Invertible scale-Conditional Function for Self-Supervised Real-world Single Image Super-Resolution—0
A Single Video Super-Resolution GAN for Multiple Downsampling Operators based on Pseudo-Inverse Image Formation Models—0
Fast Sublinear Sparse Representation using Shallow Tree Matching Pursuit—0
Identity-Preserving Pose-Robust Face Hallucination Through Face Subspace Prior—0
IEGAN: Multi-purpose Perceptual Quality Image Enhancement Using Generative Adversarial Network—0
FastSR-NeRF: Improving NeRF Efficiency on Consumer Devices with A Simple Super-Resolution Pipeline—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
Inverting a Rolling Shutter Camera: Bring Rolling Shutter Images to High Framerate Global Shutter Video—0
Fast Single Image Super-Resolution—0
Image Deconvolution with Deep Image and Kernel Priors—0
Convolutional Low-Resolution Fine-Grained Classification—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified