0000000000622616

AUTHOR

Ruifeng Zhu

showing 2 related works from this author

Learning Flow-Based Feature Warping for Face Frontalization with Illumination Inconsistent Supervision

2020

Despite recent advances in deep learning-based face frontalization methods, photo-realistic and illumination preserving frontal face synthesis is still challenging due to large pose and illumination discrepancy during training. We propose a novel Flow-based Feature Warping Model (FFWM) which can learn to synthesize photo-realistic and illumination preserving frontal images with illumination inconsistent supervision. Specifically, an Illumination Preserving Module (IPM) is proposed to learn illumination preserving image synthesis from illumination inconsistent image pairs. IPM includes two pathways which collaborate to ensure the synthesized frontal images are illumination preserving and wit…

business.industryComputer scienceDeep learningComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flow02 engineering and technology010501 environmental sciences01 natural sciencesImage (mathematics)Flow (mathematics)Feature (computer vision)Face (geometry)0202 electrical engineering electronic engineering information engineeringCode (cryptography)020201 artificial intelligence & image processingComputer visionArtificial intelligenceImage warpingbusinessComputingMethodologies_COMPUTERGRAPHICS0105 earth and related environmental sciences
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Contribution à l’apprentissage de représentation de données à base de graphes avec application à la catégorisation d’images

2020

Graph-based Manifold Learning algorithms are regarded as a powerful technique for feature extraction and dimensionality reduction in Pattern Recogniton, Computer Vision and Machine Learning fields. These algorithms utilize sample information contained in the item-item similarity and weighted matrix to reveal the intrinstic geometric structure of manifold. It exhibits the low dimensional structure in the high dimensional data. This motivates me to develop Graph-based Manifold Learning techniques on Pattern Recognition, specially, application to image categorization. The experimental datasets of thesis correspond to several categories of public image datasets such as face datasets, indoor and…

Représentation de données à base de graphesSemi supervised LearningReconnaissance de formesComputer Vision[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]Manifold LearningPattern Recognition[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]Machine LearningGraph based EmbeddingVision par ordinateurApprentissage de représentation de donnéesinformaticsApprentissage semi superviséinformáticaApprentissage machine
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