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 1701–1725 of 3874 papers

TitleStatusHype
Deep Learning based Optical Image Super-Resolution via Generative Diffusion Models for Layerwise in-situ LPBF Monitoring—0
A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolution—0
Hybrid Neural Representations for Spherical Data—0
Feature-Driven Super-Resolution for Object Detection—0
Deep learning-based super-resolution in coherent imaging systems—0
Hybrid Transformer and CNN Attention Network for Stereo Image Super-resolution—0
A Spatiotemporal Model for Precise and Efficient Fully-automatic 3D Motion Correction in OCT—0
HyperINR: A Fast and Predictive Hypernetwork for Implicit Neural Representations via Knowledge Distillation—0
Feature-based Recognition Framework for Super-resolution Images—0
Feature-domain Adaptive Contrastive Distillation for Efficient Single Image Super-Resolution—0
CoReGAN: Contrastive Regularized Generative Adversarial Network for Guided Depth Map Super Resolution—0
Feature Alignment with Equivariant Convolutions for Burst Image Super-Resolution—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
Feature Aggregating Network with Inter-Frame Interaction for Efficient Video Super-Resolution—0
FDAN: Flow-guided Deformable Alignment Network for Video Super-Resolution—0
Hyperspectral Image Super-Resolution via Dual-domain Network Based on Hybrid Convolution—0
A Sinkhorn Regularized Adversarial Network for Image Guided DEM Super-resolution using Frequency Selective Hybrid Graph Transformer—0
Hyperspectral Image Super-Resolution via Non-Local Sparse Tensor Factorization—0
3D Volumetric Super-Resolution in Radiology Using 3D RRDB-GAN—0
Integrated Super-Resolution Sensing and Communication with 5G NR Waveform: Signal Processing with Uneven CPs and Experiments—0
Interactive Image Manipulation with Complex Text Instructions—0
Hyperspectral Neural Radiance Fields—0
A full-resolution training framework for Sentinel-2 image fusion—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified