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Everything You Wanted to Know about Deep Learning for Computer Vision but Were Afraid to Ask

Ponti, Moacir Antonelli, Ribeiro, Leonardo Sampaio Ferraz, Nazare, Tiago Santana, Bui, Tu and Collomosse, John (2018) Everything You Wanted to Know about Deep Learning for Computer Vision but Were Afraid to Ask In: 30th SIBGRAPI Conference on Graphics, Patterns and Images Tutorials (SIBGRAPI-T), 17-20 Oct. 2017, Rio de Janeiro, Brazil.

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Deep Learning methods are currently the state-of-the-art in many Computer Vision and Image Processing problems, in particular image classification. After years of intensive investigation, a few models matured and became important tools, including Convolutional Neural Networks (CNNs), Siamese and Triplet Networks, Auto-Encoders (AEs) and Generative Adversarial Networks (GANs). The field is fast-paced and there is a lot of terminologies to catch up for those who want to adventure in Deep Learning waters. This paper has the objective to introduce the most fundamental concepts of Deep Learning for Computer Vision in particular CNNs, AEs and GANs, including architectures, inner workings and optimization. We offer an updated description of the theoretical and practical knowledge of working with those models. After that, we describe Siamese and Triplet Networks, not often covered in tutorial papers, as well as review the literature on recent and exciting topics such as visual stylization, pixel-wise prediction and video processing. Finally, we discuss the limitations of Deep Learning for Computer Vision.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Ponti, Moacir Antonelli
Ribeiro, Leonardo Sampaio Ferraz
Nazare, Tiago Santana
Date : 11 January 2018
DOI : 10.1109/SIBGRAPI-T.2017.12
Copyright Disclaimer : © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Uncontrolled Keywords : computer vision, deep learning, machine learning, CNN, image processing
Related URLs :
Depositing User : Melanie Hughes
Date Deposited : 18 Sep 2018 13:53
Last Modified : 19 Sep 2018 15:17

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