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 281–290 of 3874 papers

TitleStatusHype
Deep Arbitrary-Scale Image Super-Resolution via Scale-Equivariance PursuitCode1
DDet: Dual-path Dynamic Enhancement Network for Real-World Image Super-ResolutionCode1
AdaPool: Exponential Adaptive Pooling for Information-Retaining DownsamplingCode1
DDistill-SR: Reparameterized Dynamic Distillation Network for Lightweight Image Super-ResolutionCode1
DAQ: Channel-Wise Distribution-Aware Quantization for Deep Image Super-Resolution NetworksCode1
AdaDM: Enabling Normalization for Image Super-ResolutionCode1
DARTS: Double Attention Reference-based Transformer for Super-resolutionCode1
DeblurSR: Event-Based Motion Deblurring Under the Spiking RepresentationCode1
Cylin-Painting: Seamless 360 Panoramic Image Outpainting and BeyondCode1
A Benchmark for Chinese-English Scene Text Image Super-resolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified