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 2201–2250 of 3874 papers

TitleStatusHype
Cross-SRN: Structure-Preserving Super-Resolution Network with Cross Convolution—0
Cross-Spatial Pixel Integration and Cross-Stage Feature Fusion Based Transformer Network for Remote Sensing Image Super-Resolution—0
M2NO: Multiresolution Operator Learning with Multiwavelet-based Algebraic Multigrid Method—0
M^3:Manipulation Mask Manufacturer for Arbitrary-Scale Super-Resolution Mask—0
Across-scale Process Similarity based Interpolation for Image Super-Resolution—0
Machine Learning-Accelerated Computational Solid Mechanics: Application to Linear Elasticity—0
Training Your Image Restoration Network Better with Random Weight Network as Optimization Function—0
Training Your Image Restoration Network Better with Random Weight Network as Optimization Function—0
MagnifyMe: Aiding Cross Resolution Face Recognition via Identity Aware Synthesis—0
Magnitude-image based data-consistent deep learning method for MRI super resolution—0
TRAMBA: A Hybrid Transformer and Mamba Architecture for Practical Audio and Bone Conduction Speech Super Resolution and Enhancement on Mobile and Wearable Platforms—0
Cross-Scale Residual Network for Multiple Tasks:Image Super-resolution, Denoising, and Deblocking—0
Cross-MPI: Cross-scale Stereo for Image Super-Resolution using Multiplane Images—0
Mamba-based Light Field Super-Resolution with Efficient Subspace Scanning—0
Cross-Modality High-Frequency Transformer for MR Image Super-Resolution—0
MambaDS: Near-Surface Meteorological Field Downscaling with Topography Constrained Selective State Space Modeling—0
MambaLiteSR: Image Super-Resolution with Low-Rank Mamba using Knowledge Distillation—0
MAMBO: High-Resolution Generative Approach for Mammography Images—0
Manifold Based Low-rank Regularization for Image Restoration and Semi-supervised Learning—0
Tranquil Clouds: Neural Networks for Learning Temporally Coherent Features in Point Clouds—0
Manifold Modeling in Embedded Space: A Perspective for Interpreting "Deep Image Prior"—0
Manifold Modeling in Quotient Space: Learning An Invariant Mapping with Decodability of Image Patches—0
MAP-based Problem-Agnostic diffusion model for Inverse Problems—0
Mapping Low-Resolution Images To Multiple High-Resolution Images Using Non-Adversarial Mapping—0
Mapping molecular complexes with Super-Resolution Microscopy and Single-Particle Analysis—0
A Coordinate Descent Approach to Atomic Norm Denoising—0
Cross-modal Diffusion Modelling for Super-resolved Spatial Transcriptomics—0
Cross-Guided Optimization of Radiance Fields With Multi-View Image Super-Resolution for High-Resolution Novel View Synthesis—0
XCAT -- Lightweight Quantized Single Image Super-Resolution using Heterogeneous Group Convolutions and Cross Concatenation—0
Transferring Knowledge from High-Quality to Low-Quality MRI for Adult Glioma Diagnosis—0
Mathematical Foundation of Sparsity-based Multi-snapshot Spectral Estimation—0
Mathematical Theory of Computational Resolution Limit in Multi-dimensions—0
Cross-Domain Lossy Compression as Optimal Transport with an Entropy Bottleneck—0
Matrix Neural Networks—0
Matrix Variate RBM and Its Applications—0
Maximum a Posteriori on a Submanifold: a General Image Restoration Method with GAN—0
A Convex Approach for Image Hallucination—0
MaxSR: Image Super-Resolution Using Improved MaxViT—0
CRNet: Image Super-Resolution Using A Convolutional Sparse Coding Inspired Network—0
Creating Realistic Anterior Segment Optical Coherence Tomography Images using Generative Adversarial Networks—0
Measurement-Consistent Networks via a Deep Implicit Layer for Solving Inverse Problems—0
Transformation Consistency Regularization – A Semi-Supervised Paradigm for Image-to-Image Translation—0
Medical image super-resolution method based on dense blended attention network—0
Crafting Training Degradation Distribution for the Accuracy-Generalization Trade-off in Real-World Super-Resolution—0
Coupled-Projection Residual Network for MRI Super-Resolution—0
CoT-MISR:Marrying Convolution and Transformer for Multi-Image Super-Resolution—0
Meet-in-the-middle: Multi-scale upsampling and matching for cross-resolution face recognition—0
MEGAN: Memory Enhanced Graph Attention Network for Space-Time Video Super-Resolution—0
Cost-effective photonic super-resolution millimeter-wave joint radar-communication system using self-coherent detection—0
Transformer and GAN Based Super-Resolution Reconstruction Network for Medical Images—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified