Beyond the AI hype, significant new possibilities in the world of computer vision have arisen in the last few years. However, deploying computer vision solutions still requires expert vision knowledge, business understanding, solid engineering and smart processes. I’ll expose the challenges of computer vision applied to a vertical domain such as fashion, and how we solved them at Heuritech.
Charles Ollion - Heuritech
https://dataxday.fr/
Video available: https://www.youtube.com/watch?v=vg95Os_tmnk
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Background: Télécom, PhD in Machine Learning
At Université Pierre et Marie Curie
Today: Lecturer in Deep Learning at
Master Datascience Ecole Polytecnnique, EPITA
https://m2dsupsdlclass.github.io/lectures-labs/
WHO AM I?
@charlesollion
Co-Founder of Heuritech, Head of
Research
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DEEP LEARNING FOR IMAGE CLASSIFICATION
Simonyan, K., and Zisserman A. "Very deep convolutional networks for large-scale image
recognition." 2014
13. Mask R-CNN, K He, G Gkioxari, P Dollár, R Girshick, ICCV 2017
Image
Class Bounding box
INPUT OUTPUTS Segmentation masks
SEGMENTATION OF OBJECTS
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14. Mask R-CNN, K He, G Gkioxari, P Dollár, R Girshick, ICCV 2017
SEGMENTATION OF OBJECTS
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QUIZ: WHICH ONE IS HARD?
In: Traffic Sign dataset
Out: > 40 classes
In: Retina Images
Out: 2 classes
In: Instagram
Out: Bag detection
In: Shoe Photo
Out: shoe model (~500)
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DEEP LEARNING IN THE WILD
● Very broad diversity of images
● Plenty of classes
● Broad definition of each class
● Very different scales, shapes
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Our AI technology,
well-trained by experts, has reached brand new levels of performance,
precise enough to grasp the details of fashion & luxury products
IMAGE ANALYSIS AT HEURITECH
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ollion@heuritech.com charlesollion