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 611–620 of 3874 papers

TitleStatusHype
Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale Image Super-ResolutionCode0
QMambaBSR: Burst Image Super-Resolution with Query State Space Model—0
Reference-free Axial Super-resolution of 3D Microscopy Images using Implicit Neural Representation with a 2D Diffusion PriorCode0
Enhancing Events in Neutrino Telescopes through Deep Learning-Driven Super-ResolutionCode0
DIffSteISR: Harnessing Diffusion Prior for Superior Real-world Stereo Image Super-Resolution—0
GRFormer: Grouped Residual Self-Attention for Lightweight Single Image Super-ResolutionCode1
Panacea+: Panoramic and Controllable Video Generation for Autonomous DrivingCode3
One Step Diffusion-based Super-Resolution with Time-Aware DistillationCode1
Event-Stream Super Resolution using Sigma-Delta Neural Network—0
Palantir: Towards Efficient Super Resolution for Ultra-high-definition Live StreamingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified