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 2551–2600 of 3874 papers

TitleStatusHype
Perceptual cGAN for MRI Super-resolutionCode0
A Review of Deep Learning Based Image Super-resolution Techniques—0
Robust Unpaired Single Image Super-Resolution of Faces—0
SparseAlign: A Super-Resolution Algorithm for Automatic Marker Localization and Deformation Estimation in Cryo-Electron Tomography—0
Enhancement or Super-Resolution: Learning-based Adaptive Video Streaming with Client-Side Video Processing—0
Virtual Coil Augmentation Technology for MR Coil Extrapolation via Deep Learning—0
Dual Perceptual Loss for Single Image Super-Resolution Using ESRGAN—0
Improving Clinical Diagnosis Performance with Automated X-ray Scan Quality Enhancement Algorithms—0
CISRNet: Compressed Image Super-Resolution NetworkCode0
UDC: Unified DNAS for Compressible TinyML Models—0
SDT-DCSCN for Simultaneous Super-Resolution and Deblurring of Text ImagesCode0
MoViDNN: A Mobile Platform for Evaluating Video Quality Enhancement with Deep Neural NetworksCode0
SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution—0
Image quality measurements and denoising using Fourier Ring CorrelationsCode0
RestoreDet: Degradation Equivariant Representation for Object Detection in Low Resolution Images—0
Cross-SRN: Structure-Preserving Super-Resolution Network with Cross Convolution—0
Sound and Visual Representation Learning with Multiple Pretraining Tasks—0
3DVSR: 3D EPI Volume-based Approach for Angular and Spatial Light field Image Super-resolution—0
Uncovering the Over-smoothing Challenge in Image Super-Resolution: Entropy-based Quantification and Contrastive Optimization—0
Generative adversarial network for super-resolution imaging through a fiber—0
Super-resolution in Molecular Dynamics Trajectory Reconstruction with Bi-Directional Neural Networks—0
LAR-SR: A Local Autoregressive Model for Image Super-ResolutionCode0
Learning To Zoom Inside Camera Imaging Pipeline—0
SphereSR: 360deg Image Super-Resolution With Arbitrary Projection via Continuous Spherical Image Representation—0
Texture-Based Error Analysis for Image Super-Resolution—0
Neural Prior for Trajectory Estimation—0
Task Decoupled Framework for Reference-Based Super-Resolution—0
MNSRNet: Multimodal Transformer Network for 3D Surface Super-Resolution—0
A Resolution Enhancement Plug-in for Deformable Registration of Medical Images—0
Super-Efficient Super Resolution for Fast Adversarial Defense at the EdgeCode0
HPRN: Holistic Prior-embedded Relation Network for Spectral Super-ResolutionCode0
Astronomical Image Colorization and upscaling with Generative Adversarial Networks—0
DSRGAN: Detail Prior-Assisted Perceptual Single Image Super-Resolution via Generative Adversarial Networks—0
SelFSR: Self-Conditioned Face Super-Resolution in the Wild via Flow Field Degradation Network—0
Implicit Neural Representation Learning for Hyperspectral Image Super-Resolution—0
Super-resolution reconstruction of cytoskeleton image based on A-net deep learning network—0
A comparative study of paired versus unpaired deep learning methods for physically enhancing digital rock image resolution—0
Machine Learning-Accelerated Computational Solid Mechanics: Application to Linear Elasticity—0
Mitigating Channel-wise Noise for Single Image Super Resolution—0
Kernel-aware Burst Blind Super-ResolutionCode0
SphereSR: 360° Image Super-Resolution with Arbitrary Projection via Continuous Spherical Image Representation—0
Information Prebuilt Recurrent Reconstruction Network for Video Super-Resolution—0
Enhancing Multi-Scale Implicit Learning in Image Super-Resolution with Integrated Positional Encoding—0
Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction—0
γ-Net: Superresolving SAR Tomographic Inversion via Deep Learning—0
A Survey on Deep learning based Document Image Enhancement—0
Feature-based Recognition Framework for Super-resolution Images—0
Towards Super-Resolution CEST MRI for Visualization of Small StructuresCode0
Uncertainty-Driven Loss for Single Image Super-Resolution—0
Stochastic Solutions for Linear Inverse Problems using the Prior Implicit in a Denoiser—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified