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 661–670 of 3874 papers

TitleStatusHype
Gated Fusion Network for Degraded Image Super ResolutionCode1
Gated Multi-Resolution Transfer Network for Burst Restoration and EnhancementCode1
Generative AI for Rapid Diffusion MRI with Improved Image Quality, Reliability and GeneralizabilityCode1
Deterministic Image-to-Image Translation via Denoising Brownian Bridge Models with Dual ApproximatorsCode1
GenerateCT: Text-Conditional Generation of 3D Chest CT VolumesCode1
Consistent Direct Time-of-Flight Video Depth Super-ResolutionCode1
Designing a Practical Degradation Model for Deep Blind Image Super-ResolutionCode1
Generative Adversarial NetworksCode1
DEPTHOR: Depth Enhancement from a Practical Light-Weight dToF Sensor and RGB ImageCode1
DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution ModelsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified