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 976–1000 of 3874 papers

TitleStatusHype
Enhanced Super-Resolution Training via Mimicked Alignment for Real-World ScenesCode1
SVCNet: Scribble-based Video Colorization Network with Temporal AggregationCode1
End-to-end Alternating Optimization for Blind Super ResolutionCode1
EndoL2H: Deep Super-Resolution for Capsule EndoscopyCode1
DHP: Differentiable Meta Pruning via HyperNetworksCode1
End-to-end Alternating Optimization for Real-World Blind Super ResolutionCode1
SYENet: A Simple Yet Effective Network for Multiple Low-Level Vision Tasks with Real-time Performance on Mobile DeviceCode1
Blind Super-Resolution via Meta-learning and Markov Chain Monte Carlo SimulationCode1
Tackling the Ill-Posedness of Super-Resolution Through Adaptive Target GenerationCode1
Bridging Component Learning with Degradation Modelling for Blind Image Super-ResolutionCode1
Tarsier: Evolving Noise Injection in Super-Resolution GANsCode1
TDAN: Temporally Deformable Alignment Network for Video Super-ResolutionCode1
TDAN: Temporally-Deformable Alignment Network for Video Super-ResolutionCode1
Temporal Modulation Network for Controllable Space-Time Video Super-ResolutionCode1
Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: ReportCode1
Diffusion-based Blind Text Image Super-ResolutionCode1
Blockwise Parallel Decoding for Deep Autoregressive ModelsCode1
Blueprint Separable Residual Network for Efficient Image Super-ResolutionCode1
End-to-End Learning for Joint Image Demosaicing, Denoising and Super-ResolutionCode1
Enhancement of Anime Imaging Enlargement using Modified Super-Resolution CNNCode1
An efficient CNN for spectral reconstruction from RGB imagesCode1
EgoVSR: Towards High-Quality Egocentric Video Super-ResolutionCode1
Transformer for Single Image Super-ResolutionCode1
Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and ReconstructionCode1
Efficient Video Compression via Content-Adaptive Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified