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 2676–2700 of 3874 papers

TitleStatusHype
FaBiAN: A Fetal Brain magnetic resonance Acquisition Numerical phantom—0
Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution—0
Super-resolution data assimilation—0
Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral Correction and High-resolution RGB Reconstruction—0
Infrared Image Super-Resolution via Heterogeneous Convolutional WGAN—0
From Less to More: Spectral Splitting and Aggregation Network for Hyperspectral Face Super-Resolution—0
Attention-based Multi-Reference Learning for Image Super-ResolutionCode0
Super-Resolution Appearance Transfer for 4D Human Performances—0
The End Restraint Method for Mechanically Perturbing Nucleic Acids in silico—0
Multi-Attributed and Structured Text-to-Face Synthesis—0
Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search—0
Temporal Kernel Consistency for Blind Video Super-Resolution—0
SURFNet: Super-resolution of Turbulent Flows with Transfer Learning using Small Datasets—0
End-to-End Adaptive Monte Carlo Denoising and Super-Resolution—0
Seirios: Leveraging Multiple Channels for LoRaWAN Indoor and Outdoor Localization—0
FA-GAN: Fused Attentive Generative Adversarial Networks for MRI Image Super-Resolution—0
FL-MISR: Fast Large-Scale Multi-Image Super-Resolution for Computed Tomography Based on Multi-GPU Acceleration—0
Efficient Light Field Reconstruction via Spatio-Angular Dense NetworkCode0
Data Acquisition and Preparation for Dual-reference Deep Learning of Image Super-Resolution—0
Ada-VSR: Adaptive Video Super-Resolution with Meta-Learning—0
Del-Net: A Single-Stage Network for Mobile Camera ISP—0
Thermal Image Super-Resolution Using Second-Order Channel Attention with Varying Receptive FieldsCode0
Content-aware Directed Propagation Network with Pixel Adaptive Kernel Attention—0
Improving Multi-View Stereo via Super-Resolution—0
MFAGAN: A Compression Framework for Memory-Efficient On-Device Super-Resolution GAN—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified