Improving Gaze Estimation Performance Using Ensemble Loss Function
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-27199-1_51
Reference9 articles.
1. Park, S., et al.: Few-shot adaptive gaze estimation. In: 2019 IEEE/CVF International Conference on Computer Vision (ICCV), Seoul, Korea (South) (2019)
2. Krafka, K., et al.: Eye tracking for everyone. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2176–2184 (2016)
3. He, J., et al.: On-device few-shot personalization for real-time gaze estimation. In: 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), pp. 1149–1158 (2019)
4. Hajiabadi, H., Monsefi, R., Yazdi, H.S.: RELF: robust regression extended with ensemble loss function. Appl. Intell. 49(4), 1437–1450 (2018). https://doi.org/10.1007/s10489-018-1341-9
5. Bao, Y., Cheng, Y., Liu, Y., Lu, F.: Adaptive feature fusion network for gaze tracking in mobile tablets. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 9936–9943 (2021)
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