/action-anticipation-losses

Implements the loss used in A. Furnari, S. Battiato, G. M. Farinella (2018). Leveraging Uncertainty to Rethink Loss Functions and Evaluation Measures for Egocentric Action Anticipation . In International Workshop on Egocentric Perception, Interaction and Computing (EPIC) in conjunction with ECCV .

Primary LanguagePython

Video Demo

Video Demo

PyTorch Action Anticipation Losses

This repository implements the Verb-Noun Marginal Cross Entropy Loss (VNMCE) proposed in the paper (download here):

A. Furnari, S. Battiato, G. M. Farinella (2018). Leveraging Uncertainty to Rethink Loss Functions and Evaluation Measures for Egocentric Action Anticipation . In International Workshop on Egocentric Perception, Interaction and Computing (EPIC) in conjunction with ECCV.

We also report an implementation of the Truncated Top-5 Entropy Loss proposed in the paper:

Lapin, Maksim, Matthias Hein, and Bernt Schiele. "Loss functions for top-k error: Analysis and insights." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016.

Please see the code for usage examples.

Publication

Please reference this publication if you find this code useful:

@inproceedings{furnari2018Leveraging,
  author = { A. Furnari and S. Battiato and G. M. Farinella },
  title = {  Leveraging Uncertainty to Rethink Loss Functions and Evaluation Measures for Egocentric Action Anticipation  },
  booktitle = {  International Workshop on Egocentric Perception, Interaction and Computing (EPIC) in conjunction with ECCV  },
  year = { 2018 },
}

Related Works

You can find related works at the following page: http://iplab.dmi.unict.it/fpv/.