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 201–250 of 3874 papers

TitleStatusHype
Anatomically Guided Motion Correction for Placental IVIM Parameter Estimation with Accelerated Sampling Method—0
Semantic-Guided Global-Local Collaborative Networks for Lightweight Image Super-ResolutionCode0
DIPLI: Deep Image Prior Lucky Imaging for Blind Astronomical Image Restoration—0
Toward task-driven satellite image super-resolution—0
Variational Message Passing-based Multiobject Tracking for MIMO-Radars using Raw Sensor Signals—0
Involution and BSConv Multi-Depth Distillation Network for Lightweight Image Super-Resolution—0
SIR-DIFF: Sparse Image Sets Restoration with Multi-View Diffusion Model—0
CTSR: Controllable Fidelity-Realness Trade-off Distillation for Real-World Image Super Resolution—0
The Power of Context: How Multimodality Improves Image Super-Resolution—0
A super-resolution reconstruction method for lightweight building images based on an expanding feature modulation network—0
C2D-ISR: Optimizing Attention-based Image Super-resolution from Continuous to Discrete Scales—0
Rethinking Image Evaluation in Super-Resolution—0
RainScaleGAN: a Conditional Generative Adversarial Network for Rainfall DownscalingCode0
FedVSR: Towards Model-Agnostic Federated Learning in Video Super-ResolutionCode1
QDM: Quadtree-Based Region-Adaptive Sparse Diffusion Models for Efficient Image Super-ResolutionCode1
ECLARE: Efficient cross-planar learning for anisotropic resolution enhancementCode0
ReCamMaster: Camera-Controlled Generative Rendering from A Single Video—0
Toward Generalized Image Quality Assessment: Relaxing the Perfect Reference Quality AssumptionCode2
Perceive, Understand and Restore: Real-World Image Super-Resolution with Autoregressive Multimodal Generative ModelsCode2
Fourier Neural Operator based surrogates for CO_2 storage in realistic geologies—0
FourierSR: A Fourier Token-based Plugin for Efficient Image Super-Resolution—0
Automatic quality control in multi-centric fetal brain MRI super-resolution reconstructionCode1
Dual-domain Modulation Network for Lightweight Image Super-Resolution—0
SASNet: Spatially-Adaptive Sinusoidal Neural Networks—0
SuperCarver: Texture-Consistent 3D Geometry Super-Resolution for High-Fidelity Surface Detail Generation—0
Resolution Invariant Autoencoder—0
MegaSR: Mining Customized Semantics and Expressive Guidance for Image Super-ResolutionCode1
Feature Alignment with Equivariant Convolutions for Burst Image Super-Resolution—0
Reconstruct Anything Model: a lightweight foundation model for computational imaging—0
QUIET-SR: Quantum Image Enhancement Transformer for Single Image Super-Resolution—0
Over-the-Air Time-Frequency Synchronization in Distributed ISAC Systems—0
AdaptSR: Low-Rank Adaptation for Efficient and Scalable Real-World Super-Resolution—0
From Image- to Pixel-level: Label-efficient Hyperspectral Image Reconstruction—0
Boosting Diffusion-Based Text Image Super-Resolution Model Towards Generalized Real-World Scenarios—0
CATANet: Efficient Content-Aware Token Aggregation for Lightweight Image Super-ResolutionCode3
Pixel to Gaussian: Ultra-Fast Continuous Super-Resolution with 2D Gaussian Modeling—0
Emulating Self-attention with Convolution for Efficient Image Super-ResolutionCode2
GenDR: Lightning Generative Detail Restorator—0
QArtSR: Quantization via Reverse-Module and Timestep-Retraining in One-Step Diffusion based Image Super-ResolutionCode1
Global graph features unveiled by unsupervised geometric deep learning—0
DuCos: Duality Constrained Depth Super-Resolution via Foundation Model—0
Scale-Invariant Adversarial Attack against Arbitrary-scale Super-resolution—0
Improving the Temporal Resolution of SOHO/MDI Magnetograms of Solar Active Regions Using a Deep Generative Model—0
Rethinking Video Super-Resolution: Towards Diffusion-Based Methods without Motion Alignment—0
Undertrained Image Reconstruction for Realistic Degradation in Blind Image Super-Resolution—0
Volume Tells: Dual Cycle-Consistent Diffusion for 3D Fluorescence Microscopy De-noising and Super-Resolution—0
Hyperspectral Image Restoration and Super-resolution with Physics-Aware Deep Learning for Biomedical Applications—0
DifIISR: A Diffusion Model with Gradient Guidance for Infrared Image Super-ResolutionCode2
MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shiftingCode1
AutoLUT: LUT-Based Image Super-Resolution with Automatic Sampling and Adaptive Residual LearningCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified