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 1031–1040 of 3874 papers

TitleStatusHype
Image Restoration Through Generalized Ornstein-Uhlenbeck BridgeCode1
FastSR-NeRF: Improving NeRF Efficiency on Consumer Devices with A Simple Super-Resolution Pipeline—0
TMP: Temporal Motion Propagation for Online Video Super-ResolutionCode1
Guided Image Restoration via Simultaneous Feature and Image Guided Fusion—0
CartoMark: a benchmark dataset for map pattern recognition and 1 map content retrieval with machine intelligence—0
Diffusion-based Blind Text Image Super-ResolutionCode1
Video Dynamics Prior: An Internal Learning Approach for Robust Video Enhancements—0
Semantic Lens: Instance-Centric Semantic Alignment for Video Super-ResolutionCode1
EventAid: Benchmarking Event-aided Image/Video Enhancement Algorithms with Real-captured Hybrid Dataset—0
Toward Real World Stereo Image Super-Resolution via Hybrid Degradation Model and Discriminator for Implied Stereo Image InformationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified