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 2451–2500 of 3874 papers

TitleStatusHype
Feedback Pyramid Attention Networks for Single Image Super-Resolution—0
Video Super-Resolution TransformerCode1
Task Transformer Network for Joint MRI Reconstruction and Super-ResolutionCode1
Catch-A-Waveform: Learning to Generate Audio from a Single Short ExampleCode1
A self-adapting super-resolution structures framework for automatic design of GAN—0
Super-Resolution Image Reconstruction Based on Self-Calibrated Convolutional GAN—0
Variational AutoEncoder for Reference based Image Super-ResolutionCode1
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
Noise Conditional Flow Model for Learning the Super-Resolution SpaceCode1
SOUP-GAN: Super-Resolution MRI Using Generative Adversarial Networks—0
MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-ResolutionCode1
Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions—0
Robust Reference-based Super-Resolution via C2-MatchingCode1
Feedback Network for Mutually Boosted Stereo Image Super-Resolution and Disparity EstimationCode1
Accurate and Robust Deep Learning Framework for Solving Wave-Based Inverse Problems in the Super-Resolution Regime—0
Bilateral Spectrum Weighted Total Variation for Noisy-Image Super-Resolution and Image Denoising—0
Fourier Space Losses for Efficient Perceptual Image Super-Resolution—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
Pixel super-resolved lensless on-chip sensor with scattering multiplexing—0
Self-Organized Residual Blocks for Image Super-Resolution—0
CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed TomographyCode1
SNIPS: Solving Noisy Inverse Problems StochasticallyCode1
Deep Hierarchical Super Resolution for Scientific Data—0
Cascaded Diffusion Models for High Fidelity Image Generation—0
Beyond the Spectrum: Detecting Deepfakes via Re-SynthesisCode1
Blind Motion Deblurring Super-Resolution: When Dynamic Spatio-Temporal Learning Meets Static Image Understanding—0
CogView: Mastering Text-to-Image Generation via TransformersCode2
Permutation invariance and uncertainty in multitemporal image super-resolutionCode1
Low Resolution Information Also Matters: Learning Multi-Resolution Representations for Person Re-Identification—0
High-Frequency aware Perceptual Image Enhancement—0
Unpaired Depth Super-Resolution in the WildCode0
Towards Compact Single Image Super-Resolution via Contrastive Self-distillationCode1
Estimates of maize plant density from UAV RGB images using Faster-RCNN detection model: impact of the spatial resolution—0
MIASSR: An Approach for Medical Image Arbitrary Scale Super-ResolutionCode1
Extremely Lightweight Quantization Robust Real-Time Single-Image Super Resolution for Mobile DevicesCode1
Combining Transformer Generators with Convolutional Discriminators—0
Graph Convolutional Networks in Feature Space for Image Deblurring and Super-resolution—0
LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-Resolution and BeyondCode1
Content-adaptive Representation Learning for Fast Image Super-resolution—0
Anchor-based Plain Net for Mobile Image Super-ResolutionCode1
Multi-Contrast MRI Super-Resolution via a Multi-Stage Integration NetworkCode1
XCycles Backprojection Acoustic Super-Resolution—0
Automated Symbolic Law Discovery: A Computer Vision Approach—0
Improved detection of small objects in road network sequences—0
Overparametrization of HyperNetworks at Fixed FLOP-Count Enables Fast Neural Image Enhancement—0
Real-Time Video Super-Resolution on Smartphones with Deep Learning, Mobile AI 2021 Challenge: Report—0
Parallel and Flexible Sampling from Autoregressive Models via Langevin DynamicsCode1
Real-Time Quantized Image Super-Resolution on Mobile NPUs, Mobile AI 2021 Challenge: ReportCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified