Egoshots: A 2-month Ego-vision Dataset with Autographer Wearable Camera annotated "for free" with transfer learning. Three state of the art pre-trained image captioning models are used.
The dataset represents the life of 2 interns while working at Philips Research (Netherlands) (May-July 2015) generously donating their data:
- Natalia Díaz Rodríguez
- Vana Panagiotou
See associated baselines, Semantic Fidelity metric and documentation in the associated paper:
and repo:
https://github.com/Pranav21091996/Semantic_Fidelity-and-Egoshots
For research ideas, experiments and collaboration with the full dataset -this repo only includes a subset of 978 images- (including GPS, ambient light, accelerometer, magnetometer, PIR, temperature), please contact [email protected]
Thanks to Alejandro Betancourt for the Autographer camera and all rest of open-minded Eindhoven friends for being part of Vana and Natalia's stories :)
If you use it, please cite:
Egoshots, an ego-vision life-logging dataset and semantic fidelity metric to evaluate diversity in image captioning models Pranav Agarwal, Alejandro Betancourt, Vana Panagiotou, Natalia Díaz-Rodríguez. Machine Learning in Real Life (ML-IRL) ICLR 2020 Workshop https://arxiv.org/abs/2003.11743
@InProceedings{Agarwal20egoshots,
author={Pranav Agarwal and Alejandro Betancourt and Vana Panagiotou and Natalia Díaz-Rodríguez},
year={2020},
month = {Mar},
title = {Egoshots, an ego-vision life-logging dataset and semantic fidelity metric to evaluate diversity in image captioning models}
booktitle = {Machine Learning in Real Life (ML-IRL) Workshop at the International Conference on Learning Representations (ICLR)},
url={https://arxiv.org/abs/2003.11743}
}