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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2751–2775 of 3874 papers

TitleStatusHype
NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results—0
Deep Neural Network-based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions—0
Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions—0
SOUP-GAN: Super-Resolution MRI Using Generative Adversarial Networks—0
Accurate and Robust Deep Learning Framework for Solving Wave-Based Inverse Problems in the Super-Resolution Regime—0
Two-stage domain adapted training for better generalization in real-world image restoration and super-resolution—0
A survey of machine learning-based physics event generation—0
Fourier Space Losses for Efficient Perceptual Image Super-Resolution—0
Bilateral Spectrum Weighted Total Variation for Noisy-Image Super-Resolution and Image Denoising—0
Pixel super-resolved lensless on-chip sensor with scattering multiplexing—0
Self-Organized Residual Blocks for Image Super-Resolution—0
Cascaded Diffusion Models for High Fidelity Image Generation—0
Deep Hierarchical Super Resolution for Scientific Data—0
Blind Motion Deblurring Super-Resolution: When Dynamic Spatio-Temporal Learning Meets Static Image Understanding—0
Low Resolution Information Also Matters: Learning Multi-Resolution Representations for Person Re-Identification—0
High-Frequency aware Perceptual Image Enhancement—0
Estimates of maize plant density from UAV RGB images using Faster-RCNN detection model: impact of the spatial resolution—0
Unpaired Depth Super-Resolution in the WildCode0
Graph Convolutional Networks in Feature Space for Image Deblurring and Super-resolution—0
Combining Transformer Generators with Convolutional Discriminators—0
Content-adaptive Representation Learning for Fast Image Super-resolution—0
XCycles Backprojection Acoustic Super-Resolution—0
Improved detection of small objects in road network sequences—0
Overparametrization of HyperNetworks at Fixed FLOP-Count Enables Fast Neural Image Enhancement—0
Automated Symbolic Law Discovery: A Computer Vision Approach—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified