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 3751–3800 of 3874 papers

TitleStatusHype
GDCA: GAN-based single image super resolution with Dual discriminators and Channel Attention—0
GDSR: Global-Detail Integration through Dual-Branch Network with Wavelet Losses for Remote Sensing Image Super-Resolution—0
Gemino: Practical and Robust Neural Compression for Video Conferencing—0
GenDR: Lightning Generative Detail Restorator—0
E-FCNN for tiny facial expression recognition—0
Generalizable One-shot Neural Head Avatar—0
EECD-Net: Energy-Efficient Crack Detection with Spiking Neural Networks and Gated Attention—0
Edge Storage Management Recipe with Zero-Shot Data Compression for Road Anomaly Detection—0
Generalized Expectation Maximization Framework for Blind Image Super Resolution—0
Generalized Matrix-Pencil Approach to Estimation of Complex Exponentials with Gapped Data—0
Line Spectrum Estimation and Detection with Few-bit ADCs: Theoretical Analysis and Generalized NOMP Algorithm—0
Edge-SD-SR: Low Latency and Parameter Efficient On-device Super-Resolution with Stable Diffusion via Bidirectional Conditioning—0
OFDM Reference Signal Pattern Design Criteria for Integrated Communication and Sensing—0
Texture Enhancement via High-Resolution Style Transfer for Single-Image Super-Resolution—0
Deep learning-based Edge-aware pre and post-processing methods for JPEG compressed images—0
Edge-Aware Autoencoder Design for Real-Time Mixture-of-Experts Image Compression—0
Texture Hallucination for Large-Factor Painting Super-Resolution—0
eCNN: A Block-Based and Highly-Parallel CNN Accelerator for Edge Inference—0
Generating Unobserved Alternatives—0
Generative Adversarial Classifier for Handwriting Characters Super-Resolution—0
Generative Adversarial Models for Extreme Geospatial Downscaling—0
TextureWGAN: Texture Preserving WGAN with MLE Regularizer for Inverse Problems—0
Generative adversarial network for super-resolution imaging through a fiber—0
SCALES: Boost Binary Neural Network for Image Super-Resolution with Efficient Scalings—0
Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution—0
Super-Resolution Generative Adversarial Networks based Video Enhancement—0
Generative Adversarial Networks for Image Super-Resolution: A Survey—0
EAM: Enhancing Anything with Diffusion Transformers for Blind Super-Resolution—0
Generative AI in Vision: A Survey on Models, Metrics and Applications—0
A Dive into SAM Prior in Image Restoration—0
EAGLE: Large-scale Vehicle Detection Dataset in Real-World Scenarios using Aerial Imagery—0
Generative Diffusion Prior for Unified Image Restoration and Enhancement—0
A Generative Model for Generic Light Field Reconstruction—0
Generative Powers of Ten—0
Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis—0
Generator From Edges: Reconstruction of Facial Images—0
Generic 3D Convolutional Fusion for image restoration—0
Generic Perceptual Loss for Modeling Structured Output Dependencies—0
DynVideo-E: Harnessing Dynamic NeRF for Large-Scale Motion- and View-Change Human-Centric Video Editing—0
Dynamic super-resolution in particle tracking problems—0
Geometric Distortion Guided Transformer for Omnidirectional Image Super-Resolution—0
ADIR: Adaptive Diffusion for Image Reconstruction—0
Geometry-Aware Neighborhood Search for Learning Local Models for Image Reconstruction—0
Geometry-Aware Reference Synthesis for Multi-View Image Super-Resolution—0
Geometry Enhancements from Visual Content: Going Beyond Ground Truth—0
Dynamic Snake Upsampling Operater and Boundary-Skeleton Weighted Loss for Tubular Structure Segmentation—0
GHM Wavelet Transform for Deep Image Super Resolution—0
A Deep Residual Star Generative Adversarial Network for multi-domain Image Super-Resolution—0
GIMP-ML: Python Plugins for using Computer Vision Models in GIMP—0
GITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential Equations—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified