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 391–400 of 3874 papers

TitleStatusHype
ARM: Any-Time Super-Resolution MethodCode1
DynaVSR: Dynamic Adaptive Blind Video Super-ResolutionCode1
Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image AttenuationCode1
Decoupled Data Consistency with Diffusion Purification for Image RestorationCode1
Augmented Convolutional LSTMs for Generation of High-Resolution Climate Change ProjectionsCode1
AdaPool: Exponential Adaptive Pooling for Information-Retaining DownsamplingCode1
Deep Adaptive Inference Networks for Single Image Super-ResolutionCode1
DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable DiffusionCode1
Collaborative Feedback Discriminative Propagation for Video Super-ResolutionCode1
Collapsible Linear Blocks for Super-Efficient Super ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified