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 2326–2350 of 3874 papers

TitleStatusHype
Motion Guided LIDAR-camera Self-calibration and Accelerated Depth Upsampling for Autonomous Vehicles—0
Transport-based analysis, modeling, and learning from signal and data distributions—0
MPRNet: Multi-Path Residual Network for Lightweight Image Super Resolution—0
MPSI: Mamba enhancement model for pixel-wise sequential interaction Image Super-Resolution—0
Transport-Based Single Frame Super Resolution of Very Low Resolution Face Images—0
MR Image Denoising and Super-Resolution Using Regularized Reverse Diffusion—0
MR Image Super-Resolution With Squeeze and Excitation Reasoning Attention Network—0
MR imaging in the low-field: Leveraging the power of machine learning—0
Confidence-aware Levenberg-Marquardt optimization for joint motion estimation and super-resolution—0
Transthoracic super-resolution ultrasound localisation microscopy of myocardial vasculature in patients—0
MRI Super-Resolution with Ensemble Learning and Complementary Priors—0
MRI Super-Resolution with GAN and 3D Multi-Level DenseNet: Smaller, Faster, and Better—0
MrSARP: A Hierarchical Deep Generative Prior for SAR Image Super-resolution—0
Trilevel Neural Architecture Search for Efficient Single Image Super-Resolution—0
MSCE: An edge preserving robust loss function for improving super-resolution algorithms—0
MSCrackMamba: Leveraging Vision Mamba for Crack Detection in Fused Multispectral Imagery—0
MSECG: Incorporating Mamba for Robust and Efficient ECG Super-Resolution—0
TriNeRFLet: A Wavelet Based Triplane NeRF Representation—0
MSRA-SR: Image Super-resolution Transformer with Multi-scale Shared Representation Acquisition—0
MTKD: Multi-Teacher Knowledge Distillation for Image Super-Resolution—0
Conditioning 3D Diffusion Models with 2D Images: Towards Standardized OCT Volumes through En Face-Informed Super-Resolution—0
Conditioned Regression Models for Non-Blind Single Image Super-Resolution—0
Multi-Attention Generative Adversarial Network for Remote Sensing Image Super-Resolution—0
Multi-Attributed and Structured Text-to-Face Synthesis—0
Multi-bin Trainable Linear Unit for Fast Image Restoration Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified