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 2351–2400 of 3874 papers

TitleStatusHype
Lightweight Spatial-Channel Adaptive Coordination of Multilevel Refinement Enhancement Network for Image Reconstruction—0
Dynamics-informed deconvolutional neural networks for super-resolution identification of regime changes in epidemiological time seriesCode0
A Spatiotemporal Model for Precise and Efficient Fully-automatic 3D Motion Correction in OCT—0
Inductive Matrix Completion and Root-MUSIC-Based Channel Estimation for Intelligent Reflecting Surface (IRS)-Aided Hybrid MIMO Systems—0
Realistic Hair Synthesis with Generative Adversarial Networks—0
OAIR: Object-Aware Image Retargeting Using PSO and Aesthetic Quality AssessmentCode0
A Multi-Task Learning Model for Super Resolution of Wireless Channel Characteristics—0
Magnitude-image based data-consistent deep learning method for MRI super resolution—0
Video Restoration with a Deep Plug-and-Play Prior—0
Deep filter bank regression for super-resolution of anisotropic MR brain images—0
Time-domain speech super-resolution with GAN based modeling for telephony speaker verification—0
Quasi-supervised Learning for Super-resolution PETCode0
ELSR: Extreme Low-Power Super Resolution Network For Mobile DevicesCode0
XCAT -- Lightweight Quantized Single Image Super-Resolution using Heterogeneous Group Convolutions and Cross Concatenation—0
QuantNAS for super resolution: searching for efficient quantization-friendly architectures against quantization noiseCode0
Laplacian Pyramid-like AutoencoderCode0
3D Super-Resolution Ultrasound with Adaptive Weight-Based Beamforming—0
Maximum Likelihood on the Joint (Data, Condition) Distribution for Solving Ill-Posed Problems with Conditional Flow ModelsCode0
Time-lapse image classification using a diffractive neural network—0
Towards Robust Drone Vision in the Wild—0
Trustworthy modelling of atmospheric formaldehyde powered by deep learning—0
Extreme-scale Talking-Face Video Upsampling with Audio-Visual PriorsCode0
Multi-dimensional topological loss for cortical plate segmentation in fetal brain MRI—0
Urban precipitation downscaling using deep learning: a smart city application over Austin, Texas, USA—0
An Adversarial Generative Network Designed for High-Resolution Monocular Depth Estimation from 2D HiRISE Images of MarsCode0
Global Priors Guided Modulation Network for Joint Super-Resolution and Inverse Tone-Mapping—0
G-PCC Post-Processing Using Fractional Super-Resolution—0
Online Video Super-Resolution with Convolutional Kernel Bypass Graft—0
H2-Stereo: High-Speed, High-Resolution Stereoscopic Video System—0
Latent Multi-Relation Reasoning for GAN-Prior based Image Super-Resolution—0
Pyramidal Denoising Diffusion Probabilistic Models—0
High Dynamic Range and Super-Resolution from Raw Image Bursts—0
Criteria Comparative Learning for Real-scene Image Super-ResolutionCode0
Learning Series-Parallel Lookup Tables for Efficient Image Super-ResolutionCode0
REPNP: Plug-and-Play with Deep Reinforcement Learning Prior for Robust Image Restoration—0
Edge-Aware Autoencoder Design for Real-Time Mixture-of-Experts Image Compression—0
Sparse-based Domain Adaptation Network for OCTA Image Super-Resolution Reconstruction—0
Learning Generalizable Latent Representations for Novel Degradations in Super Resolution—0
Sub-Aperture Feature Adaptation in Single Image Super-resolution Model for Light Field Imaging—0
Enhancing Image Rescaling using Dual Latent Variables in Invertible Neural NetworkCode0
Improved Super Resolution of MR Images Using CNNs and Vision Transformers—0
Calcium oscillation on homogeneous and heterogeneous networks of ryanodine receptor—0
Semantic uncertainty intervals for disentangled latent spacesCode0
Efficient Meta-Tuning for Content-aware Neural Video DeliveryCode0
Flow-based Visual Quality Enhancer for Super-resolution Magnetic Resonance Spectroscopic ImagingCode0
HSE-NN Team at the 4th ABAW Competition: Multi-task Emotion Recognition and Learning from Synthetic Images—0
Geometry-Aware Reference Synthesis for Multi-View Image Super-Resolution—0
Learning Knowledge Representation with Meta Knowledge Distillation for Single Image Super-Resolution—0
Stochastic Attribute Modeling for Face Super-Resolution—0
Untrained, physics-informed neural networks for structured illumination microscopy—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified