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CoPE: Conditional image generation using Polynomial Expansions
Generative modeling has evolved to a notable field of machine learning. ...
04/11/2021 ∙ by Grigorios G. Chrysos, et al. ∙
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Unsupervised Controllable Generation with Self-Training
Recent generative adversarial networks (GANs) are able to generate impre...
07/17/2020 ∙ by Grigorios G. Chrysos, et al. ∙
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Π-nets: Deep Polynomial Neural Networks
Deep Convolutional Neural Networks (DCNNs) is currently the method of ch...
03/08/2020 ∙ by Grigorios G. Chrysos, et al. ∙
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Reconstructing the Noise Manifold for Image Denoising
Deep Convolutional Neural Networks (DCNNs) have been successfully used i...
02/11/2020 ∙ by Ioannis Marras, et al. ∙
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Robust Conditional Generative Adversarial Networks
Conditional generative adversarial networks (cGAN) have led to large imp...
05/22/2018 ∙ by Grigorios G. Chrysos, et al. ∙
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Motion deblurring of faces
Face analysis is a core part of computer vision, in which remarkable pro...
03/08/2018 ∙ by Grigorios G. Chrysos, et al. ∙
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Visual Data Augmentation through Learning
The rapid progress in machine learning methods has been empowered by i) ...
01/20/2018 ∙ by Grigorios G. Chrysos, et al. ∙
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Deep Face Deblurring
Blind deblurring consists a long studied task, however the outcomes of g...
04/27/2017 ∙ by Grigorios G. Chrysos, et al. ∙
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A Comprehensive Performance Evaluation of Deformable Face Tracking "In-the-Wild"
Recently, technologies such as face detection, facial landmark localisat...
03/18/2016 ∙ by Grigorios G. Chrysos, et al. ∙
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