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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2376–2400 of 3874 papers

TitleStatusHype
HyperINR: A Fast and Predictive Hypernetwork for Implicit Neural Representations via Knowledge Distillation—0
Hyper-Restormer: A General Hyperspectral Image Restoration Transformer for Remote Sensing Imaging—0
HyperSound: Generating Implicit Neural Representations of Audio Signals with Hypernetworks—0
Hyperspectral Image Restoration and Super-resolution with Physics-Aware Deep Learning for Biomedical Applications—0
Hyperspectral Image Super-Resolution in Arbitrary Input-Output Band Settings—0
Hyperspectral Image Super-resolution via Deep Spatio-spectral Convolutional Neural Networks—0
Hyperspectral Image Super-Resolution via Dual-domain Network Based on Hybrid Convolution—0
Hyperspectral Image Super-Resolution via Non-Local Sparse Tensor Factorization—0
Hyperspectral Neural Radiance Fields—0
Hyperspectral Spatial Super-Resolution using Keystone Error—0
Hyperspectral Super-Resolution: A Coupled Tensor Factorization Approach—0
Hyperspectral Super-resolution: A Coupled Nonnegative Block-term Tensor Decomposition Approach—0
Hyperspectral Super-Resolution by Coupled Spectral Unmixing—0
Hyperspectral Super-Resolution via Interpretable Block-Term Tensor Modeling—0
Hyperspectral Super-Resolution via Coupled Tensor Ring Factorization—0
HypervolGAN: An efficient approach for GAN with multi-objective training function—0
ICF-SRSR: Invertible scale-Conditional Function for Self-Supervised Real-world Single Image Super-Resolution—0
Cross-resolution Face Recognition via Identity-Preserving Network and Knowledge Distillation—0
Identity-Preserving Pose-Robust Face Hallucination Through Face Subspace Prior—0
IEGAN: Multi-purpose Perceptual Quality Image Enhancement Using Generative Adversarial Network—0
IFF: A Super-resolution Algorithm for Multiple Measurements—0
IGAF: Incremental Guided Attention Fusion for Depth Super-Resolution—0
Image-based Synthesis and Re-Synthesis of Viewpoints Guided by 3D Models—0
Image Deconvolution with Deep Image and Kernel Priors—0
Image Denoising and Super-Resolution using Residual Learning of Deep Convolutional Network—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified