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 2351–2400 of 3874 papers

TitleStatusHype
Memory-Augmented Non-Local Attention for Video Super-ResolutionCode1
edge-SR: Super-Resolution For The MassesCode1
SwinIR: Image Restoration Using Swin TransformerCode3
Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search—0
Thermal Image Processing via Physics-Inspired Deep NetworksCode1
Deep Reparametrization of Multi-Frame Super-Resolution and DenoisingCode1
Temporal Kernel Consistency for Blind Video Super-Resolution—0
Light Field Image Super-Resolution with TransformersCode1
spectrai: A deep learning framework for spectral dataCode1
SURFNet: Super-resolution of Turbulent Flows with Transfer Learning using Small Datasets—0
Seirios: Leveraging Multiple Channels for LoRaWAN Indoor and Outdoor Localization—0
End-to-End Adaptive Monte Carlo Denoising and Super-Resolution—0
Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-ResolutionCode1
Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image RescalingCode1
FL-MISR: Fast Large-Scale Multi-Image Super-Resolution for Computed Tomography Based on Multi-GPU Acceleration—0
FA-GAN: Fused Attentive Generative Adversarial Networks for MRI Image Super-Resolution—0
Efficient Light Field Reconstruction via Spatio-Angular Dense NetworkCode0
Ada-VSR: Adaptive Video Super-Resolution with Meta-Learning—0
Data Acquisition and Preparation for Dual-reference Deep Learning of Image Super-Resolution—0
Del-Net: A Single-Stage Network for Mobile Camera ISP—0
Finding Discriminative Filters for Specific Degradations in Blind Super-ResolutionCode1
Discovering Distinctive "Semantics" in Super-Resolution NetworksCode1
Thermal Image Super-Resolution Using Second-Order Channel Attention with Varying Receptive FieldsCode0
Fourier Series Expansion Based Filter Parametrization for Equivariant ConvolutionsCode1
Improving Multi-View Stereo via Super-Resolution—0
Content-aware Directed Propagation Network with Pixel Adaptive Kernel Attention—0
BridgeNet: A Joint Learning Network of Depth Map Super-Resolution and Monocular Depth Estimation—0
MFAGAN: A Compression Framework for Memory-Efficient On-Device Super-Resolution GAN—0
Crack Segmentation for Low-Resolution Images using Joint Learning with Super-ResolutionCode1
LAConv: Local Adaptive Convolution for Image Fusion—0
Self-Conditioned Probabilistic Learning of Video RescalingCode1
Compressed Ultrasound Imaging:from Sub-Nyquist Rates to Super-Resolution—0
Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic DataCode4
High-Resolution Pelvic MRI Reconstruction Using a Generative Adversarial Network with Attention and Cyclic Loss—0
RankSRGAN: Super Resolution Generative Adversarial Networks with Learning to Rank—0
Joint Implicit Image Function for Guided Depth Super-ResolutionCode1
ProfileSR-GAN: A GAN based Super-Resolution Method for Generating High-Resolution Load Profiles—0
Joint Semi-supervised 3D Super-Resolution and Segmentation with Mixed Adversarial Gaussian Domain Adaptation—0
Level generation and style enhancement -- deep learning for game development overview—0
Multi-Attention Generative Adversarial Network for Remote Sensing Image Super-Resolution—0
Single-shot structured illumination microscopy—0
Real-Time Super-Resolution System of 4K-Video Based on Deep LearningCode1
Learned super resolution ultrasound for improved breast lesion characterization—0
Effectiveness of State-of-the-Art Super Resolution Algorithms in Surveillance Environment—0
Image restoration quality assessment based on regional differential information entropy—0
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation—0
Deep Learning Based Autonomous Vehicle Super Resolution DOA Estimation for Safety Driving—0
Blind Image Super-Resolution: A Survey and Beyond—0
A comparative study of various Deep Learning techniques for spatio-temporal Super-Resolution reconstruction of Forced Isotropic Turbulent flows—0
A Deep Residual Star Generative Adversarial Network for multi-domain Image Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified