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REFERENCES

1 
Alletto S., Palazzi A., Solera F., Calderara. S., Cucchiara R., 2016, DR(eye)VE: A Dataset for Attention-Based Tasks with Applications to Autonomous and Assisted Driving, 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 54-60DOI
2 
Tawari. A., Kang B., 2017, A Computational Framework for Driver's Visual Attention Using a Fully Convolutional Architecture, 2017 IEEE Intelligent Vehicles Symposium (IV), pp. 887-894DOI
3 
Palazzi A., Solera F., Calderara S., Alletto. S., Cucchiara R., 2017, Learning Where to Attend Like a Human Driver, 2017 IEEE Intelligent Vehicles Symposium (IV), pp. 920-925DOI
4 
Palazzi A., Abati D., Calderara S., Solera. F., Cucchiara R., July 2019, Predicting the Driver's Focus of Attention: The DR(eye)VE Project, in IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 41, No. 7, pp. 1720-1733DOI
5 
Xia Y., Zhang D., Kim J., Nakayama K., Zipser K., Whitney D., 2019, Predicting Driver Attention in Critical Situations, in Computer Vision - ACCV 2018, Lecture Notes in Computer Science, Vol. 11365DOI
6 
Fang J., Yan D., Qiao J., Xue J., Wang. H., Li S., 2019, DADA-2000: Can Driving Accident be Predicted by Driver Attention${\mathit{f}}$ Analyzed by A Benchmark, 2019 IEEE Intelligent Transportation Systems Conference (ITSC), pp. 4303-4309DOI
7 
Fang J., Yan D., Qiao J., Xue. J., Yu H., 2021, DADA: Driver Attention Prediction in Driving Accident Scenarios, in IEEE Transactions on Intelligent Transportation SystemsDOI
8 
Li A., 2017, Learning Driver Gaze, M. Eng thesisGoogle Search
9 
Ning M., Lu. C., Gong J., 2019, An Efficient Model for Driving Focus of Attention Prediction using Deep Learning, 2019 IEEE Intelligent Transportation Systems Conference (ITSC), pp. 1192-1197DOI
10 
Kang. B., Lee Y., Apr. 2020., High-Resolution Neural Network for Driver Visual Attention Prediction, Sensors, Vol. 20, No. 7, pp. 2030DOI
11 
Kang. B., Lee Y., May 2021., A Driver's Visual Attention Prediction Using Optical Flow, Sensors, Vol. 21, No. 11, pp. 3722DOI
12 
Nakazawa. S., Nakada Y., 2020, Improvement of Mixture-of-Experts-Type Model to Construct Dynamic Saliency Maps for Predicting Drivers' Attention, 2020 IEEE Symposium Series on Computational Intelligence (SSCI)DOI
13 
Lv K., Sheng H., Xiong Z., Li. W., Zheng L., 2021, Improving Driver Gaze Prediction with Reinforced Attention, in IEEE Transactions on MultimediaDOI
14 
Itti L., Koch. C., Niebur E., Nov. 1998, A Model of Saliency-Based Visual Attention for Rapid Scene Analysis, in IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No. 11, pp. 1254-1259DOI
15 
Harel J., Koch. C., Perona P., 2007, Graph-based Visual Saliency, in Advances in Neural Information Processing Systems 19, MIT Press, pp. 545-552Google Search
16 
Wang J., Sun K., Cheng T., Jiang B., Deng C., Zhao Y., Liu D., Mu Y., Tan M., Wang X., Liu W., Xiao B., Oct. 2021, Deep High-Resolution Representation Learning for Visual Recognition, in IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 43, No. 10, pp. 3349-3364DOI
17 
Farnebäck G., 2003, Two-Frame Motion Estimation Based on Polynomial Expansion, in Scandinavian Conference on Image Analysis, Lecture Notes in Computer Science, SpringerDOI