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 976–1000 of 3874 papers

TitleStatusHype
Discovering Distinctive "Semantics" in Super-Resolution NetworksCode1
Model-Based Deep LearningCode1
Make-A-Video: Text-to-Video Generation without Text-Video DataCode1
Diffusion Prior Interpolation for Flexibility Real-World Face Super-ResolutionCode1
DiMoSR: Feature Modulation via Multi-Branch Dilated Convolutions for Efficient Image Super-ResolutionCode1
The Devil is in the Details: Boosting Guided Depth Super-Resolution via Rethinking Cross-Modal Alignment and AggregationCode1
Bridging Component Learning with Degradation Modelling for Blind Image Super-ResolutionCode1
Blind Super-Resolution via Meta-learning and Markov Chain Monte Carlo SimulationCode1
MambaCSR: Dual-Interleaved Scanning for Compressed Image Super-Resolution With SSMsCode1
Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: ReportCode1
mdctGAN: Taming transformer-based GAN for speech super-resolution with Modified DCT spectraCode1
MDCN: Multi-scale Dense Cross Network for Image Super-ResolutionCode1
MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-ResolutionCode1
DiSR-NeRF: Diffusion-Guided View-Consistent Super-Resolution NeRFCode1
MAT: Multi-Range Attention Transformer for Efficient Image Super-ResolutionCode1
Model-Guided Multi-Contrast Deep Unfolding Network for MRI Super-resolution ReconstructionCode1
Diffusion-based Blind Text Image Super-ResolutionCode1
Blueprint Separable Residual Network for Efficient Image Super-ResolutionCode1
An efficient CNN for spectral reconstruction from RGB imagesCode1
Diffusion Model Based Posterior Sampling for Noisy Linear Inverse ProblemsCode1
MegaSR: Mining Customized Semantics and Expressive Guidance for Image Super-ResolutionCode1
Towards Real Scene Super-Resolution with Raw ImagesCode1
Towards Real-Time 4K Image Super-ResolutionCode1
DSR: Towards Drone Image Super-ResolutionCode1
Diffusion Models Beat GANs on Image ClassificationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified