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 2751–2800 of 3874 papers

TitleStatusHype
Super-resolution of periodic signals from short sequences of samples—0
Non-convex Super-resolution of OCT images via sparse representation—0
Face Hallucination via Split-Attention in Split-Attention NetworkCode1
Deep Learning for Efficient Reconstruction of High-Resolution Turbulent DNS DataCode1
Adaptive Pixel-wise Structured Sparse Network for Efficient CNNs—0
Micro CT Image-Assisted Cross Modality Super-Resolution of Clinical CT Images Utilizing Synthesized Training Dataset—0
Multi-Modal Super Resolution for Dense Microscopic Particle Size Estimation—0
Fourier Neural Operator for Parametric Partial Differential EquationsCode2
Boosting High-Level Vision with Joint Compression Artifacts Reduction and Super-Resolution—0
Light Stage Super-Resolution: Continuous High-Frequency Relighting—0
VolumeNet: A Lightweight Parallel Network for Super-Resolution of Medical Volumetric Data—0
A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery—0
Morphological Reconstruction Improves Microvessel Mapping in Super-Resolution Ultrasound—0
AI-assisted super-resolution cosmological simulations—0
LASSR: Effective Super-Resolution Method for Plant Disease Diagnosis—0
Neural Enhancement in Content Delivery Systems: The State-of-the-Art and Future Directions—0
Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 NetworkCode1
Diagnosing and Preventing Instabilities in Recurrent Video Processing—0
Attaining Real-Time Super-Resolution for Microscopic Images Using GANCode1
WDN: A Wide and Deep Network to Divide-and-Conquer Image Super-resolution—0
ASDN: A Deep Convolutional Network for Arbitrary Scale Image Super-ResolutionCode0
Unfolding the Alternating Optimization for Blind Super ResolutionCode1
AFN: Attentional Feedback Network based 3D Terrain Super-ResolutionCode0
Spatial Frequency Bias in Convolutional Generative Adversarial Networks—0
Efficient Image Super-Resolution Using Pixel AttentionCode1
High Quality Remote Sensing Image Super-Resolution Using Deep Memory Connected Network—0
Deformable Kernel Convolutional Network for Video Extreme Super-Resolution—0
FAN: Frequency Aggregation Network for Real Image Super-resolution—0
AIM 2020 Challenge on Video Temporal Super-Resolution—0
High-throughput molecular imaging via deep learning enabled Raman spectroscopyCode1
Interpretable Detail-Fidelity Attention Network for Single Image Super-ResolutionCode1
ADMM-Net for Communication Interference Removal in Stepped-Frequency Radar—0
Deep Selective Combinatorial Embedding and Consistency Regularization for Light Field Super-resolution—0
Blind Image Super-Resolution with Spatial Context Hallucination—0
Tarsier: Evolving Noise Injection in Super-Resolution GANsCode1
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results—0
Deep Artifact-Free Residual Network for Single Image Super-Resolution—0
Residual Feature Distillation Network for Lightweight Image Super-ResolutionCode1
GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain ConnectomesCode1
Augmented Convolutional LSTMs for Generation of High-Resolution Climate Change ProjectionsCode1
Local-Global Fusion Network for Video Super-ResolutionCode1
NEMO: enabling neural-enhanced video streaming on commodity mobile devicesCode1
Reconstruct high-resolution multi-focal plane images from a single 2D wide field image—0
AdderSR: Towards Energy Efficient Image Super-Resolution—0
DeepRemaster: Temporal Source-Reference Attention Networks for Comprehensive Video Enhancement—0
Searching for Low-Bit Weights in Quantized Neural NetworksCode1
Parallax Attention for Unsupervised Stereo Correspondence LearningCode1
Multiple Exemplars-based Hallucinationfor Face Super-resolution and Editing—0
AIM 2020 Challenge on Efficient Super-Resolution: Methods and ResultsCode2
Understanding Deformable Alignment in Video Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified