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 1351–1375 of 3874 papers

TitleStatusHype
A Generative Model for Generic Light Field Reconstruction—0
A Unified Plug-and-Play Algorithm with Projected Landweber Operator for Split Convex Feasibility Problems—0
AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results—0
Generative Powers of Ten—0
Deep Blind Hyperspectral Image Fusion—0
AccDecoder: Accelerated Decoding for Neural-enhanced Video Analytics—0
A unified method for super-resolution recovery and real exponential-sum separation—0
PINNs for Medical Image Analysis: A Survey—0
MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors—0
Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis—0
Generic Perceptual Loss for Modeling Structured Output Dependencies—0
Geometry Enhancements from Visual Content: Going Beyond Ground Truth—0
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation—0
A Unified Framework to Super-Resolve Face Images of Varied Low Resolutions—0
A Boosting Method to Face Image Super-resolution—0
Augmenting Perceptual Super-Resolution via Image Quality Predictors—0
Deep Attentive Generative Adversarial Network for Photo-Realistic Image De-Quantization—0
Deep Artifact-Free Residual Network for Single Image Super-Resolution—0
Deep Appearance Models: A Deep Boltzmann Machine Approach for Face Modeling—0
Augmented Equivariant Attention Networks for Microscopy Image Reconstruction—0
Generative AI in Vision: A Survey on Models, Metrics and Applications—0
Deep 3D World Models for Multi-Image Super-Resolution Beyond Optical Flow—0
AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models—0
Decoupling Multi-Contrast Super-Resolution: Pairing Unpaired Synthesis with Implicit Representations—0
AI-Driven HSI: Multimodality, Fusion, Challenges, and the Deep Learning Revolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified