NVGaze: An Anatomically-Informed Dataset for Low-Latency, Near-Eye Gaze Estimation

Joohwan Kim, Michael Stengel, Alexander Majercik, Shalini De Mello, David Dunn, Samuli Laine, Morgan McGuire, David Luebke. NVGaze: An Anatomically-Informed Dataset for Low-Latency, Near-Eye Gaze Estimation. In Stephen A. Brewster, Geraldine Fitzpatrick, Anna L. Cox, Vassilis Kostakos, editors, Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, CHI 2019, Glasgow, Scotland, UK, May 04-09, 2019. pages 550, ACM, 2019. [doi]

@inproceedings{KimSMMDLML19,
  title = {NVGaze: An Anatomically-Informed Dataset for Low-Latency, Near-Eye Gaze Estimation},
  author = {Joohwan Kim and Michael Stengel and Alexander Majercik and Shalini De Mello and David Dunn and Samuli Laine and Morgan McGuire and David Luebke},
  year = {2019},
  doi = {10.1145/3290605.3300780},
  url = {https://doi.org/10.1145/3290605.3300780},
  researchr = {https://researchr.org/publication/KimSMMDLML19},
  cites = {0},
  citedby = {0},
  pages = {550},
  booktitle = {Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, CHI 2019, Glasgow, Scotland, UK, May 04-09, 2019},
  editor = {Stephen A. Brewster and Geraldine Fitzpatrick and Anna L. Cox and Vassilis Kostakos},
  publisher = {ACM},
  isbn = {978-1-4503-5970-2},
}