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Unsupervised Learning from Narrated Instruction Videos

Jean-Baptiste Alayrac 1, 2, 3 Piotr Bojanowski 2, 4 Nishant Agrawal 1, 2, 5 Josef Sivic 4, 2 Ivan Laptev 2 Simon Lacoste-Julien 1, 6, 3
2 WILLOW - Models of visual object recognition and scene understanding
CNRS - Centre National de la Recherche Scientifique : UMR8548, Inria Paris-Rocquencourt, DI-ENS - Département d'informatique de l'École normale supérieure
3 SIERRA - Statistical Machine Learning and Parsimony
DI-ENS - Département d'informatique de l'École normale supérieure, ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR8548
Abstract : We address the problem of automatically learning the main steps to complete a certain task, such as changing a car tire, from a set of narrated instruction videos. The contributions of this paper are three-fold. First, we develop a new unsupervised learning approach that takes advantage of the complementary nature of the input video and the associated narration. The method solves two clustering problems, one in text and one in video, applied one after each other and linked by joint constraints to obtain a single coherent sequence of steps in both modalities. Second, we collect and annotate a new challenging dataset of real-world instruction videos from the Internet. The dataset contains about 800,000 frames for five different tasks that include complex interactions between people and objects, and are captured in a variety of indoor and outdoor settings. Third, we experimentally demonstrate that the proposed method can automatically discover, in an unsupervised manner, the main steps to achieve the task and locate the steps in the input videos.
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Contributor : Jean-Baptiste Alayrac <>
Submitted on : Friday, July 3, 2015 - 10:03:01 AM
Last modification on : Wednesday, January 30, 2019 - 11:07:59 AM

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  • HAL Id : hal-01171193, version 1
  • ARXIV : 1506.09215



Jean-Baptiste Alayrac, Piotr Bojanowski, Nishant Agrawal, Josef Sivic, Ivan Laptev, et al.. Unsupervised Learning from Narrated Instruction Videos. CVPR2016 - 29th IEEE Conference on Computer Vision and Pattern Recognition, Jun 2016, Las Vegas, United States. ⟨hal-01171193⟩



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