A Self Validation Network for Object-Level Human Attention Estimation

This site is for the NeurIPS paper:

A Self Validation Network for Object-Level Human Attention Estimation

If you find materials here helpful, consider cite:

@inproceedings{attention2019neurips,
   title = { A Self Validation Network for Object-Level Human Attention Estimation },
    author = {Zehua Zhang and Chen Yu and David Crandall},
    booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
    year = {2019}
}

The site is UNDER CONSTRUCTION.

However, code and a draft poster is available at:
https://github.com/zehzhang/MindreaderNet-Mr.-Net-

The IU Computer Vision Lab's projects and activities have been funded, in part, by grants and contracts from the Air Force Office of Scientific Research (AFOSR), the Defense Threat Reduction Agency (DTRA), Dzyne Technologies, EgoVid, Inc., ETRI, Facebook, Google, Grant Thornton LLP, IARPA, the Indiana Innovation Institute (IN3), the IU Data to Insight Center, the IU Office of the Vice Provost for Research through an Emerging Areas of Research grant, the IU Social Sciences Research Commons, the Lilly Endowment, NASA, National Science Foundation (IIS-1253549, CNS-1834899, CNS-1408730, BCS-1842817, CNS-1744748, IIS-1257141, IIS-1852294), NVidia, ObjectVideo, Office of Naval Research (ONR), Pixm, Inc., and the U.S. Navy. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the U.S. Government, or any sponsor.