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 2801–2850 of 3874 papers

TitleStatusHype
T2 Mapping from Super-Resolution-Reconstructed Clinical Fast Spin Echo Magnetic Resonance Acquisitions—0
Taming Stable Diffusion for Computed Tomography Blind Super-Resolution—0
TANet: A new Paradigm for Global Face Super-resolution via Transformer-CNN Aggregation Network—0
Task-Aware Image Downscaling—0
Task Decoupled Framework for Reference-Based Super-Resolution—0
Task-driven real-world super-resolution of document scans—0
Task-driven single-image super-resolution reconstruction of document scans—0
Task-Driven Super Resolution: Object Detection in Low-resolution Images—0
TcGAN: Semantic-Aware and Structure-Preserved GANs with Individual Vision Transformer for Fast Arbitrary One-Shot Image Generation—0
Tchebichef Transform Domain-based Deep Learning Architecture for Image Super-resolution—0
Co-learning Single-Step Diffusion Upsampler and Downsampler with Two Discriminators and Distillation—0
Teacher-Student Network for Real-World Face Super-Resolution with Progressive Embedding of Edge Information—0
TEMImageNet Training Library and AtomSegNet Deep-Learning Models for High-Precision Atom Segmentation, Localization, Denoising, and Super-Resolution Processing of Atomic-Resolution Images—0
Temporal and Spatial Super Resolution with Latent Diffusion Model in Medical MRI images—0
Temporal Kernel Consistency for Blind Video Super-Resolution—0
Temporal shape super-resolution by intra-frame motion encoding using high-fps structured light—0
Temporal Super-Resolution using Multi-Channel Illumination Source—0
Tensor Decompositions for Hyperspectral Data Processing in Remote Sensing: A Comprehensive Review—0
Tensor-Generative Adversarial Network with Two-dimensional Sparse Coding: Application to Real-time Indoor Localization—0
Test-Time Adaptation for Super-Resolution: You Only Need to Overfit on a Few More Images—0
Test-time Cost-and-Quality Controllable Arbitrary-Scale Super-Resolution with Variable Fourier Components—0
Test-time Training for Hyperspectral Image Super-resolution—0
Text-guided Explorable Image Super-resolution—0
TextIR: A Simple Framework for Text-based Editable Image Restoration—0
S^3Mamba: Arbitrary-Scale Super-Resolution via Scaleable State Space Model—0
TextSR: Diffusion Super-Resolution with Multilingual OCR Guidance—0
Texture-Based Error Analysis for Image Super-Resolution—0
Texture Enhancement via High-Resolution Style Transfer for Single-Image Super-Resolution—0
Texture Hallucination for Large-Factor Painting Super-Resolution—0
TextureWGAN: Texture Preserving WGAN with MLE Regularizer for Inverse Problems—0
The Domain Transform Solver—0
The End Restraint Method for Mechanically Perturbing Nucleic Acids in silico—0
Medical Image Super-Resolution Using a Generative Adversarial Network—0
Theoretical Perspectives on Deep Learning Methods in Inverse Problems—0
Theory of Generative Deep Learning : Probe Landscape of Empirical Error via Norm Based Capacity Control—0
The Perception-Robustness Tradeoff in Deterministic Image Restoration—0
The Power of Context: How Multimodality Improves Image Super-Resolution—0
ThermalNeRF: Thermal Radiance Fields—0
Thermodynamics-informed super-resolution of scarce temporal dynamics data—0
Thermographic detection of internal defects using 2D photothermal super resolution reconstruction with sequential laser heating—0
Think Twice Before You Act: Improving Inverse Problem Solving With MCMC—0
Three-dimensional Optical Coherence Tomography Image Denoising through Multi-input Fully-Convolutional Networks—0
Three more Decades in Array Signal Processing Research: An Optimization and Structure Exploitation Perspective—0
Time accelerated image super-resolution using shallow residual feature representative network—0
Time-domain speech super-resolution with GAN based modeling for telephony speaker verification—0
Time Efficient Training of Progressive Generative Adversarial Network using Depthwise Separable Convolution and Super Resolution Generative Adversarial Network—0
Time-lapse image classification using a diffractive neural network—0
Time-series Initialization and Conditioning for Video-agnostic Stabilization of Video Super-Resolution using Recurrent Networks—0
SPIRE: Semantic Prompt-Driven Image Restoration—0
TMSR: Tiny Multi-path CNNs for Super Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified