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 3691–3700 of 3874 papers

TitleStatusHype
Denoiser-based projections for 2-D super-resolution multi-reference alignmentCode0
Hybrid Residual Attention Network for Single Image Super ResolutionCode0
Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale Image Super-ResolutionCode0
RefSR-NeRF: Towards High Fidelity and Super Resolution View SynthesisCode0
Hybrid Inexact BCD for Coupled Structured Matrix Factorization in Hyperspectral Super-ResolutionCode0
Deformable Non-local Network for Video Super-ResolutionCode0
Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion CompensationCode0
Hybrid Function Sparse Representation towards Image Super ResolutionCode0
Region-Conditioned Orthogonal 3D U-Net for Weather4Cast CompetitionCode0
StairwayGraphNet for Inter- and Intra-modality Multi-resolution Brain Graph Alignment and SynthesisCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified