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Generating Videos of Zero-Shot Compositions of Actions and Objects

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Computer Vision – ECCV 2020 (ECCV 2020)

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Abstract

Human activity videos involve rich, varied interactions between people and objects. In this paper we develop methods for generating such videos – making progress toward addressing the important, open problem of video generation in complex scenes. In particular, we introduce the task of generating human-object interaction videos in a zero-shot compositional setting, i.e., generating videos for action-object compositions that are unseen during training, having seen the target action and target object separately. This setting is particularly important for generalization in human activity video generation, obviating the need to observe every possible action-object combination in training and thus avoiding the combinatorial explosion involved in modeling complex scenes. To generate human-object interaction videos, we propose a novel adversarial framework HOI-GAN which includes multiple discriminators focusing on different aspects of a video. To demonstrate the effectiveness of our proposed framework, we perform extensive quantitative and qualitative evaluation on two challenging datasets: EPIC-Kitchens and 20BN-Something-Something v2.

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Acknowledgements

This work was done when Megha Nawhal was an intern at Borealis AI. We would like to thank the Borealis AI team for participating in our user study.

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Authors and Affiliations

  1. Borealis AI, Vancouver, Canada

    Megha Nawhal, Andreas Lehrmann, Leonid Sigal & Greg Mori

  2. Simon Fraser University, Burnaby, Canada

    Megha Nawhal, Mengyao Zhai & Greg Mori

  3. University of British Columbia, Vancouver, Canada

    Leonid Sigal

  4. Vector Institute for AI, Toronto, Canada

    Leonid Sigal

  5. CIFAR AI Chair, Toronto, Canada

    Leonid Sigal

Authors
  1. Megha Nawhal
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  2. Mengyao Zhai
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  3. Andreas Lehrmann
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  4. Leonid Sigal
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  5. Greg Mori
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Correspondence to Megha Nawhal .

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Editors and Affiliations

  1. University of Oxford, Oxford, UK

    Andrea Vedaldi

  2. Graz University of Technology, Graz, Austria

    Horst Bischof

  3. University of Freiburg, Freiburg im Breisgau, Germany

    Thomas Brox

  4. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Jan-Michael Frahm

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Nawhal, M., Zhai, M., Lehrmann, A., Sigal, L., Mori, G. (2020). Generating Videos of Zero-Shot Compositions of Actions and Objects. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, JM. (eds) Computer Vision – ECCV 2020. ECCV 2020. Lecture Notes in Computer Science(), vol 12357. Springer, Cham. https://doi.org/10.1007/978-3-030-58610-2_23

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