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 1901–1950 of 3874 papers

TitleStatusHype
Iterative-in-Iterative Super-Resolution Biomedical Imaging Using One Real Image—0
Deep Unrolled Network for Video Super-Resolution—0
Iterative Reweighted Least Squares Networks With Convergence Guarantees for Solving Inverse Imaging Problems—0
Deep unfolding Network for Hyperspectral Image Super-Resolution with Automatic Exposure Correction—0
Deep Unfolded Robust PCA with Application to Clutter Suppression in Ultrasound—0
Towards a Sampling Theory for Implicit Neural Representations—0
ITSRN++: Stronger and Better Implicit Transformer Network for Continuous Screen Content Image Super-Resolution—0
JDSR-GAN: Constructing An Efficient Joint Learning Network for Masked Face Super-Resolution—0
J-Net: Improved U-Net for Terahertz Image Super-Resolution—0
Joint Angle and Velocity-Estimation for Target Localization in Bistatic mmWave MIMO Radar in the Presence of Clutter—0
Joint convolutional neural pyramid for depth map super-resolution—0
Deep Super-Resolution Network for Single Image Super-Resolution with Realistic Degradations—0
Joint Demosaicing and Super-Resolution (JDSR): Network Design and Perceptual Optimization—0
Joint Dictionary Learning for Example-based Image Super-resolution—0
Joint Estimation of Camera Pose, Depth, Deblurring, and Super-Resolution from a Blurred Image Sequence—0
Joint Face Completion and Super-resolution using Multi-scale Feature Relation Learning—0
Joint Face Hallucination and Deblurring via Structure Generation and Detail Enhancement—0
Joint Face Super-Resolution and Deblurring Using a Generative Adversarial Network—0
Joint Flow And Feature Refinement Using Attention For Video Restoration—0
Joint Generative Learning and Super-Resolution For Real-World Camera-Screen Degradation—0
Towards Bidirectional Arbitrary Image Rescaling: Joint Optimization and Cycle Idempotence—0
Deep super resolution crack network (SrcNet) for improving computer vision–based automated crack detectability in in situ bridges—0
DeepSUM++: Non-local Deep Neural Network for Super-Resolution of Unregistered Multitemporal Images—0
Deep Spectral Prior—0
Joint Low-level and High-level Textual Representation Learning with Multiple Masking Strategies—0
Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing—0
Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement—0
Towards Clip-Free Quantized Super-Resolution Networks: How to Tame Representative Images—0
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation—0
Joint MR sequence optimization beats pure neural network approaches for spin-echo MRI super-resolution—0
Joint Multiple FMCW Chirp Sequence Processing for Velocity Estimation and Ambiguity Resolving—0
Joint Multitarget Detection and Tracking with mmWave Radar—0
Joint OAM Radar-Communication Systems: Target Recognition and Beam Optimization—0
Joint Range-Velocity-Azimuth Estimation for OFDM-Based Integrated Sensing and Communication—0
Adaptive Transform Domain Image Super-resolution Via Orthogonally Regularized Deep Networks—0
Joint Semi-supervised 3D Super-Resolution and Segmentation with Mixed Adversarial Gaussian Domain Adaptation—0
Joint Spatial and Angular Super-Resolution from a Single Image—0
Joint-SRVDNet: Joint Super Resolution and Vehicle Detection Network—0
Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution—0
Towards Content-Independent Multi-Reference Super-Resolution: Adaptive Pattern Matching and Feature Aggregation—0
When Super-Resolution Meets Camouflaged Object Detection: A Comparison Study—0
Joint Super-Resolution and Rectification for Solar Cell Inspection—0
Joint Super-Resolution and Segmentation for 1-m Impervious Surface Area Mapping in China's Yangtze River Economic Belt—0
Deep Selective Combinatorial Embedding and Consistency Regularization for Light Field Super-resolution—0
DeepSD: Generating High Resolution Climate Change Projections through Single Image Super-Resolution—0
Adaptive Pixel-wise Structured Sparse Network for Efficient CNNs—0
Kalman-Inspired Feature Propagation for Video Face Super-Resolution—0
Deep Sampling Networks—0
Deep Residual Networks with a Fully Connected Recon-struction Layer for Single Image Super-Resolution—0
Deep Residual Axial Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified