What Actions are Needed for Understanding Human Actions in Videos?

@article{Sigurdsson2017WhatAA,
  title={What Actions are Needed for Understanding Human Actions in Videos?},
  author={Gunnar A. Sigurdsson and Olga Russakovsky and A. Gupta},
  journal={2017 IEEE International Conference on Computer Vision (ICCV)},
  year={2017},
  pages={2156-2165}
}
  • Gunnar A. Sigurdsson, Olga Russakovsky, A. Gupta
  • Published 2017
  • Computer Science
  • 2017 IEEE International Conference on Computer Vision (ICCV)
  • What is the right way to reason about human activities? What directions forward are most promising? In this work, we analyze the current state of human activity understanding in videos. The goal of this paper is to examine datasets, evaluation metrics, algorithms, and potential future directions. We look at the qualitative attributes that define activities such as pose variability, brevity, and density. The experiments consider multiple state-of-the-art algorithms and multiple datasets. The… CONTINUE READING
    85 Citations

    Figures and Topics from this paper

    Explore Further: Topics Discussed in This Paper

    Am I Done? Predicting Action Progress in Videos
    • 21
    • PDF
    CATER: A diagnostic dataset for Compositional Actions and TEmporal Reasoning
    • 18
    • PDF
    Weakly Supervised Gaussian Networks for Action Detection
    • 6
    • PDF
    Temporal Relational Reasoning in Videos
    • 338
    • PDF
    Zero-shot Recognition of Complex Action Sequences
    VideoGraph: Recognizing Minutes-Long Human Activities in Videos
    • 11
    • PDF
    Structured Learning for Action Recognition in Videos
    Generating Videos of Zero-Shot Compositions of Actions and Objects
    • 1
    • PDF

    References

    SHOWING 1-10 OF 44 REFERENCES
    Learning realistic human actions from movies
    • 3,412
    • PDF
    Asynchronous Temporal Fields for Action Recognition
    • 113
    • PDF
    A combined pose, object, and feature model for action understanding
    • 62
    Recognizing realistic actions from videos “in the wild”
    • 918
    • PDF
    ActivityNet: A large-scale video benchmark for human activity understanding
    • 856
    • Highly Influential
    • PDF
    Detecting activities of daily living in first-person camera views
    • 592
    • PDF
    Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos
    • 235
    • PDF
    HMDB: A large video database for human motion recognition
    • 1,939
    • PDF
    Machine Recognition of Human Activities: A Survey
    • 1,342
    • PDF
    ActionVLAD: Learning Spatio-Temporal Aggregation for Action Classification
    • 262
    • PDF