Chen et al., 2021 - Google Patents
The face image super-resolution algorithm based on combined representation learningChen et al., 2021
- Document ID
- 1720689086602903949
- Author
- Chen Y
- Phonevilay V
- Tao J
- Chen X
- Xia R
- Zhang Q
- Yang K
- Xiong J
- Xie J
- Publication year
- Publication venue
- Multimedia Tools and Applications
External Links
Snippet
Face super-resolution reconstruction is the process of predicting high-resolution face images from one or more observed low-resolution face images, which is a typical pathological problem. As a domain-specific super-resolution task, we can use facial priori …
- 238000004422 calculation algorithm 0 title description 36
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30861—Retrieval from the Internet, e.g. browsers
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2200/00—Indexing scheme for image data processing or generation, in general
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T9/00—Image coding, e.g. from bit-mapped to non bit-mapped
- G06T9/001—Model-based coding, e.g. wire frame
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Chen et al. | The face image super-resolution algorithm based on combined representation learning | |
Liu et al. | SCCGAN: style and characters inpainting based on CGAN | |
CN111047548B (en) | Attitude transformation data processing method and device, computer equipment and storage medium | |
Yan et al. | Fine-grained attention and feature-sharing generative adversarial networks for single image super-resolution | |
Huang et al. | Sparse self-attention transformer for image inpainting | |
Li et al. | Learning face image super-resolution through facial semantic attribute transformation and self-attentive structure enhancement | |
Chauhan et al. | Deep learning-based single-image super-resolution: A comprehensive review | |
CN112884758B (en) | Defect insulator sample generation method and system based on style migration method | |
Liu et al. | Dual learning-based graph neural network for remote sensing image super-resolution | |
Liu et al. | Features guided face super-resolution via hybrid model of deep learning and random forests | |
Chen et al. | Towards real-world blind face restoration with generative diffusion prior | |
Tomar et al. | Deep hyfeat based attention in attention model for face super-resolution | |
Zhou et al. | A superior image inpainting scheme using Transformer-based self-supervised attention GAN model | |
Li et al. | Image super-resolution reconstruction based on multi-scale dual-attention | |
Chen et al. | Robust face super-resolution via position relation model based on global face context | |
Sharma et al. | An efficient image super resolution model with dense skip connections between complex filter structures in Generative Adversarial Networks | |
Chen et al. | Hybrid attention fusion embedded in transformer for remote sensing image semantic segmentation | |
Campana et al. | Variable-hyperparameter visual transformer for efficient image inpainting | |
Yu et al. | MagConv: Mask-guided convolution for image inpainting | |
Jiang et al. | Tcgan: Semantic-aware and structure-preserved gans with individual vision transformer for fast arbitrary one-shot image generation | |
Li et al. | A review of advances in image inpainting research | |
Zhuang et al. | Dimensional transformation mixer for ultra-high-definition industrial camera dehazing | |
Sun et al. | Facial mask attention network for identity-aware face super-resolution | |
Sharma et al. | Multilevel progressive recursive dilated networks with correlation filter (MPRDNCF) for image super-resolution | |
Miao et al. | Chinese font migration combining local and global features learning |