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 251–275 of 3874 papers

TitleStatusHype
Deep Face Super-Resolution with Iterative Collaboration between Attentive Recovery and Landmark EstimationCode1
Deep Burst Super-ResolutionCode1
Accelerating Diffusion Models for Inverse Problems through Shortcut SamplingCode1
Diffusion Models Beat GANs on Image ClassificationCode1
Deep Blind Super-Resolution for Satellite VideoCode1
Adaptive Local Implicit Image Function for Arbitrary-scale Super-resolutionCode1
Deep Blind Video Super-resolutionCode1
Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-ResolutionCode1
Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-ResolutionCode1
Deep Arbitrary-Scale Image Super-Resolution via Scale-Equivariance PursuitCode1
Deep Adaptive Inference Networks for Single Image Super-ResolutionCode1
Deep Audio Waveform PriorCode1
Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image AttenuationCode1
Decoupled Data Consistency with Diffusion Purification for Image RestorationCode1
DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable DiffusionCode1
DA-MUSIC: Data-Driven DoA Estimation via Deep Augmented MUSIC AlgorithmCode1
DeblurSR: Event-Based Motion Deblurring Under the Spiking RepresentationCode1
DDistill-SR: Reparameterized Dynamic Distillation Network for Lightweight Image Super-ResolutionCode1
Decomposition-Based Variational Network for Multi-Contrast MRI Super-Resolution and ReconstructionCode1
DARTS: Double Attention Reference-based Transformer for Super-resolutionCode1
Adaptive Cross-Layer Attention for Image RestorationCode1
DDet: Dual-path Dynamic Enhancement Network for Real-World Image Super-ResolutionCode1
DeepBedMap: Using a deep neural network to better resolve the bed topography of AntarcticaCode1
Deep Image PriorCode1
CVAE-GAN: Fine-Grained Image Generation through Asymmetric TrainingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified