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Pré-Publication, Document De Travail Année : 2020

Leveraging the Present to Anticipate the Future in Videos

Résumé

Anticipating actions before they are executed is crucial for a wide range of practical applications including autonomous driving and robotics. While most prior work in this area requires partial observation of executed actions , in the paper we focus on anticipating actions seconds before they start. Our proposed approach is the fusion of a purely anticipatory model with a complementary model constrained to reason about the present. In particular, the latter predicts present action and scene attributes , and reasons about how they evolve over time. By doing so, we aim at modeling action anticipation at a more conceptual level than directly predicting future actions. Our model outperforms previously reported methods on the EPIC-KITCHENS and Breakfast datasets.
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Dates et versions

hal-02433506 , version 1 (30-01-2020)

Identifiants

  • HAL Id : hal-02433506 , version 1

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Antoine Miech, Ivan Laptev, Josef Sivic, Heng Wang, Lorenzo Torresani, et al.. Leveraging the Present to Anticipate the Future in Videos. 2020. ⟨hal-02433506⟩
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