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 201–225 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
The Power of Context: How Multimodality Improves 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
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
RainScaleGAN: a Conditional Generative Adversarial Network for Rainfall DownscalingCode0
Rethinking Image Evaluation in Super-Resolution—0
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
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
ReCamMaster: Camera-Controlled Generative Rendering from A Single Video—0
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
Resolution Invariant Autoencoder—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified