Action Anticipation with Goal Consistency

In this paper, we address the problem of short-term action anticipation, i.e., we want to predict an upcoming action one second before it happens. We propose to harness high-level intent information to anticipate actions that will take place in the future. To this end, we incorporate an additional goal prediction branch into our model and propose a consistency loss function that encourages the anticipated actions to conform to the high-level goal pursued in the video. In our experiments, we show the effectiveness of the proposed approach and demonstrate that our method achieves state-of-the-art results on two large-scale datasets: Assembly101 and COIN. The code is available at https://github.com/olga-zats/goal_consistency.

  • Published in:
    International Conference on Image Processing
  • Type:
    Inproceedings
  • Authors:
    Zatsarynna, Olga; Gall, Jürgen
  • Year:
    2023

Citation information

Zatsarynna, Olga; Gall, Jürgen: Action Anticipation with Goal Consistency, International Conference on Image Processing, 2023, https://ieeexplore.ieee.org/document/10222914, Zatsarynna.Gall.2023a,

Associated Lamarr Researchers

lamarr institute person Gall Juergen - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Prof. Dr. Jürgen Gall

Principal Investigator Embodied AI to the profile