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 1251–1300 of 3874 papers

TitleStatusHype
A Self-Supervised Deep Denoiser for Hyperspectral and Multispectral Image FusionCode0
Iterative Reweighted Least Squares Networks With Convergence Guarantees for Solving Inverse Imaging Problems—0
HSD-PAM: High Speed Super Resolution Deep Penetration Photoacoustic Microscopy Imaging Boosted by Dual Branch Fusion Network—0
Exploring Frequency-Inspired Optimization in Transformer for Efficient Single Image Super-ResolutionCode1
Harnessing Artificial Intelligence To Reduce Phototoxicity in Live Imaging—0
When Super-Resolution Meets Camouflaged Object Detection: A Comparison Study—0
PSRFlow: Probabilistic Super Resolution with Flow-Based Models for Scientific Data—0
A Benchmark for Chinese-English Scene Text Image Super-resolutionCode1
Dual Aggregation Transformer for Image Super-ResolutionCode2
All-in-one Multi-degradation Image Restoration Network via Hierarchical Degradation Representation—0
NNVISR: Bring Neural Network Video Interpolation and Super Resolution into Video Processing FrameworkCode1
High-Resolution Vision Transformers for Pixel-Level Identification of Structural Components and Damage—0
DiffDance: Cascaded Human Motion Diffusion Model for Dance Generation—0
One-stage Low-resolution Text Recognition with High-resolution Knowledge TransferCode1
Unfolding Once is Enough: A Deployment-Friendly Transformer Unit for Super-ResolutionCode1
Neural Poisson Surface Reconstruction: Resolution-Agnostic Shape Reconstruction from Point CloudsCode1
Super-Resolution Estimation of UWB Channels including the Diffuse Component -- An SBL-Inspired Approach—0
Efficient neural supersampling on a novel gaming dataset—0
Lightweight Super-Resolution Head for Human Pose EstimationCode1
HiREN: Towards Higher Supervision Quality for Better Scene Text Image Super-Resolution—0
StarSRGAN: Improving Real-World Blind Super-ResolutionCode1
Fully 11 Convolutional Network for Lightweight Image Super-ResolutionCode1
RGB-D-Fusion: Image Conditioned Depth Diffusion of Humanoid SubjectsCode0
Recovering high-quality FODs from a reduced number of diffusion-weighted images using a model-driven deep learning architectureCode0
A full-resolution training framework for Sentinel-2 image fusion—0
The RoboDepth Challenge: Methods and Advancements Towards Robust Depth EstimationCode2
SuperInpaint: Learning Detail-Enhanced Attentional Implicit Representation for Super-resolutional Image Inpainting—0
ESSAformer: Efficient Transformer for Hyperspectral Image Super-resolutionCode1
Overcoming Distribution Mismatch in Quantizing Image Super-Resolution NetworksCode0
Bayesian Based Unrolling for Reconstruction and Super-resolution of Single-Photon Lidar Systems—0
ICF-SRSR: Invertible scale-Conditional Function for Self-Supervised Real-world Single Image Super-Resolution—0
CycMuNet+: Cycle-Projected Mutual Learning for Spatial-Temporal Video Super-Resolution—0
ResShift: Efficient Diffusion Model for Image Super-resolution by Residual ShiftingCode3
On the Effectiveness of Spectral Discriminators for Perceptual Quality ImprovementCode1
Real-Time Neural Video Recovery and Enhancement on Mobile Devices—0
NLCUnet: Single-Image Super-Resolution Network with Hairline Details—0
PartDiff: Image Super-resolution with Partial Diffusion Models—0
Frequency-aware optical coherence tomography image super-resolution via conditional generative adversarial neural network—0
Towards Robust Scene Text Image Super-resolution via Explicit Location EnhancementCode1
Soft-IntroVAE for Continuous Latent space Image Super-Resolution—0
A comparative analysis of SRGAN models—0
Real-time Inference and Extrapolation via a Diffusion-inspired Temporal Transformer Operator (DiTTO)—0
DARTS: Double Attention Reference-based Transformer for Super-resolutionCode1
Reconstructed Convolution Module Based Look-Up Tables for Efficient Image Super-ResolutionCode1
Diffusion Models Beat GANs on Image ClassificationCode1
Surface Geometry Processing: An Efficient Normal-based Detail Representation—0
MoTIF: Learning Motion Trajectories with Local Implicit Neural Functions for Continuous Space-Time Video Super-ResolutionCode1
MaxSR: Image Super-Resolution Using Improved MaxViT—0
Reconstructing Three-decade Global Fine-Grained Nighttime Light Observations by a New Super-Resolution Framework—0
Local Conditional Neural Fields for Versatile and Generalizable Large-Scale Reconstructions in Computational ImagingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified