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 2151–2200 of 3874 papers

TitleStatusHype
Exploring Strengths and Weaknesses of Super-Resolution Attack in Deepfake Detection—0
Exploring the solution space of linear inverse problems with GAN latent geometry—0
FaBiAN: A Fetal Brain magnetic resonance Acquisition Numerical phantom—0
Face Hallucination by Attentive Sequence Optimization with Reinforcement Learning—0
Face hallucination using cascaded super-resolution and identity priors—0
Face Hallucination using Linear Models of Coupled Sparse Support—0
Face Recognition in Low Quality Images: A Survey—0
Face Super-resolution Guided by Facial Component Heatmaps—0
Face Super-Resolution with Progressive Embedding of Multi-scale Face Priors—0
Face to Cartoon Incremental Super-Resolution using Knowledge Distillation—0
Facial Attribute Capsules for Noise Face Super Resolution—0
Facial Expression Restoration Based on Improved Graph Convolutional Networks—0
FADPNet: Frequency-Aware Dual-Path Network for Face Super-Resolution—0
FA-GAN: Fused Attentive Generative Adversarial Networks for MRI Image Super-Resolution—0
Fair Primal Dual Splitting Method for Image Inverse Problems—0
FaithDiff: Unleashing Diffusion Priors for Faithful Image Super-resolution—0
FAN: Feature Adaptation Network for Surveillance Face Recognition and Normalization—0
FAN: Frequency Aggregation Network for Real Image Super-resolution—0
FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution—0
FAST: A Framework to Accelerate Super-Resolution Processing on Compressed Videos—0
Fast and Accurate Image Upscaling With Super-Resolution Forests—0
Fast and Light-Weight Network for Single Frame Structured Illumination Microscopy Super-Resolution—0
Fast and selective super-resolution ultrasound in vivo with sono-switchable nanodroplets—0
Fast Image Deconvolution using Hyper-Laplacian Priors—0
Fast Image Super-Resolution Based on In-Place Example Regression—0
Fast Neural Architecture Search for Lightweight Dense Prediction Networks—0
Fast Online Video Super-Resolution with Deformable Attention Pyramid—0
Fast Randomized-MUSIC for mm-Wave Massive MIMO Radars—0
Fast Single Image Super-Resolution—0
Fast single image super-resolution based on sigmoid transformation—0
Fast Spatio-Temporal Residual Network for Video Super-Resolution—0
FastSR-NeRF: Improving NeRF Efficiency on Consumer Devices with A Simple Super-Resolution Pipeline—0
Fast Sublinear Sparse Representation using Shallow Tree Matching Pursuit—0
FB-HyDON: Parameter-Efficient Physics-Informed Operator Learning of Complex PDEs via Hypernetwork and Finite Basis Domain Decomposition—0
FDAN: Flow-guided Deformable Alignment Network for Video Super-Resolution—0
Feature Aggregating Network with Inter-Frame Interaction for Efficient Video Super-Resolution—0
Feature Alignment with Equivariant Convolutions for Burst Image Super-Resolution—0
Feature-domain Adaptive Contrastive Distillation for Efficient Single Image Super-Resolution—0
Feature-based Recognition Framework for Super-resolution Images—0
Feature-Driven Super-Resolution for Object Detection—0
Feature Representation Matters: End-to-End Learning for Reference-based Image Super-resolution—0
Feature Super-Resolution Based Facial Expression Recognition for Multi-scale Low-Resolution Faces—0
Feature Super-Resolution: Make Machine See More Clearly—0
Federated Learning for Blind Image Super-Resolution—0
Feedback Graph Attention Convolutional Network for Medical Image Enhancement—0
Feedback Neural Network based Super-resolution of DEM for generating high fidelity features—0
Feedback Pyramid Attention Networks for Single Image Super-Resolution—0
Improving Few-shot Learning by Spatially-aware Matching and CrossTransformer—0
A Close Look at Few-shot Real Image Super-resolution from the Distortion Relation Perspective—0
FFEINR: Flow Feature-Enhanced Implicit Neural Representation for Spatio-temporal Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified