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

Showing 781790 of 3874 papers

TitleStatusHype
A Two-Stage Attentive Network for Single Image Super-ResolutionCode1
Burstormer: Burst Image Restoration and Enhancement TransformerCode1
A New Dataset and Framework for Real-World Blurred Images Super-ResolutionCode1
BurstM: Deep Burst Multi-scale SR using Fourier Space with Optical FlowCode1
Deep Image PriorCode1
iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection NetworksCode1
iSeeBetter: Spatio-temporal video super-resolution using recurrent generative back-projection networksCode1
DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable DiffusionCode1
Gated Multi-Resolution Transfer Network for Burst Restoration and EnhancementCode1
Iterative Soft Shrinkage Learning for Efficient Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41Unverified