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 876–900 of 3874 papers

TitleStatusHype
Attaining Real-Time Super-Resolution for Microscopic Images Using GANCode1
Unfolding the Alternating Optimization for Blind Super ResolutionCode1
Efficient Image Super-Resolution Using Pixel AttentionCode1
High-throughput molecular imaging via deep learning enabled Raman spectroscopyCode1
Interpretable Detail-Fidelity Attention Network for Single Image Super-ResolutionCode1
Tarsier: Evolving Noise Injection in Super-Resolution GANsCode1
Residual Feature Distillation Network for Lightweight Image Super-ResolutionCode1
Augmented Convolutional LSTMs for Generation of High-Resolution Climate Change ProjectionsCode1
GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain ConnectomesCode1
Local-Global Fusion Network for Video Super-ResolutionCode1
NEMO: enabling neural-enhanced video streaming on commodity mobile devicesCode1
Searching for Low-Bit Weights in Quantized Neural NetworksCode1
Parallax Attention for Unsupervised Stereo Correspondence LearningCode1
Enhanced Quadratic Video InterpolationCode1
Hyperspectral Image Super-Resolution via Deep Prior Regularization with Parameter EstimationCode1
Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-ResolutionCode1
Plug-and-Play Image Restoration with Deep Denoiser PriorCode1
MDCN: Multi-scale Dense Cross Network for Image Super-ResolutionCode1
Multi-Attention Based Ultra Lightweight Image Super-ResolutionCode1
Edge and Identity Preserving Network for Face Super-ResolutionCode1
Multi-Dimension Fusion Network for Light Field Spatial Super-Resolution using Dynamic FiltersCode1
Deep Variational Network Toward Blind Image RestorationCode1
Exploit Camera Raw Data for Video Super-Resolution via Hidden Markov Model InferenceCode1
A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-ResolutionCode1
Single Image Super-Resolution via a Holistic Attention NetworkCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified