distraction_detection.md

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Scene gaze  | In-vehicle gaze  | Distraction detection  | Drowsiness detection  | Action anticipation  | Driver awareness  | Self-driving  | Papers with code  

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Click on each entry below to see additional information.

Hu et al., Human-Centric Context and Self-Uncertainty-Driven Multi-Modal Large Language Model for Training-Free Vision-Based Driver State Recognition, Trans. ITS, 2025 | paper

Dataset(s): AIDE, 3MDAD

@article{2025_T-ITS_Hu,
    author = "Hu, Chuanfei and Li, Xinde",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "Human-Centric Context and Self-Uncertainty-Driven Multi-Modal Large Language Model for Training-Free Vision-Based Driver State Recognition",
    year = "2025"
}

Tamura et al., Cognitive Distraction Detection Using Gaze and Pupil with an Interpretable Approach, IV, 2025 | paper | code

Dataset(s): private

@inproceedings{2025_IV_Tamura,
    author = "Tamura, Kimimasa and Stent, Simon and Gideon, John and Shintani, Kohei and Rosman, Guy",
    booktitle = "2025 IEEE Intelligent Vehicles Symposium (IV)",
    organization = "IEEE",
    pages = "1305--1312",
    title = "Cognitive Distraction Detection Using Gaze and Pupil with an Interpretable Approach",
    year = "2025"
}

Chi et al., VLM-DM: Visual Language Models for Multitask Domain Adaptation in Driver Monitoring, IV, 2025 | paper

Dataset(s): NTHU-DDD

@inproceedings{2025_IV_Chi,
    author = "Chi, Haozhuang and Yang, Haohan and Yang, Lie and Lv, Chen",
    booktitle = "2025 IEEE Intelligent Vehicles Symposium (IV)",
    organization = "IEEE",
    pages = "1280--1285",
    title = "VLM-DM: Visual Language Models for Multitask Domain Adaptation in Driver Monitoring",
    year = "2025"
}

Yang et al., Quantitative Identification of Driver Distraction: A Weakly Supervised Contrastive Learning Approach, Trans. ITS, 2024 | paper | code

Dataset(s): 3MDAD, AUCD2, SAM-DD

@article{2024_T-ITS_Yang,
    author = "Yang, Haohan and Liu, Haochen and Hu, Zhongxu and Nguyen, Anh-Tu and Guerra, Thierry-Marie and Lv, Chen",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "Quantitative identification of driver distraction: A weakly supervised contrastive learning approach",
    year = "2023"
}

Li et al., Domain Adaptive Driver Distraction Detection Based on Partial Feature Alignment and Confusion-Minimized Classification, Trans. ITS, 2024 | paper

Dataset(s): SFDDD, AUCD2

@article{2024_T-ITS_Li_2,
    author = "Li, Guofa and Wang, Guanglei and Guo, Zizheng and Liu, Qing and Luo, Xiyuan and Yuan, Bangwei and Li, Mingrui and Yang, Lu",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "Domain Adaptive Driver Distraction Detection Based on Partial Feature Alignment and Confusion-Minimized Classification",
    year = "2024"
}

Li et al., A Lightweight and Efficient Distracted Driver Detection Model Fusing Convolutional Neural Network and Vision Transformer, Trans. ITS, 2024 | paper | code

Dataset(s): SFDDD, 100-Driver

@article{2024_T-ITS_Li_1,
    author = "Li, Zhao and Zhao, Xia and Wu, Fuwei and Chen, Dan and Wang, Chang",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "A Lightweight and Efficient Distracted Driver Detection Model Fusing Convolutional Neural Network and Vision Transformer",
    year = "2024"
}

Li et al., Domain Adaptive Driver Distraction Detection Based on Partial Feature Alignment and Confusion-Minimized Classification, Trans. ITS, 2024 | paper

Dataset(s): SFDDD, AUCD2

@article{2024_T-ITS_Li,
    author = "Li, Guofa and Wang, Guanglei and Guo, Zizheng and Liu, Qing and Luo, Xiyuan and Yuan, Bangwei and Li, Mingrui and Yang, Lu",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "Domain Adaptive Driver Distraction Detection Based on Partial Feature Alignment and Confusion-Minimized Classification",
    year = "2024"
}

Hu et al., An Investigation of the Effect of Smart Cockpit Layout on Distracted Driving Behavior Based on Real Road Experiments, Trans. ITS, 2024 | paper

Dataset(s): private

@article{2024_T-ITS_Hu_1,
    author = "Hu, Lin and Deng, Xinjiao and Wang, Fang and Wu, Xianhui",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "An Investigation of the Effect of Smart Cockpit Layout on Distracted Driving Behavior Based on Real Road Experiments",
    year = "2024"
}

Hasan et al., Vision-Language Models Can Identify Distracted Driver Behavior From Naturalistic Videos, Trans. ITS, 2024 | paper | code

Dataset(s): DMD, SAM-DD, SFDDD, SynDD1

@article{2024_T-ITS_Hasan,
    author = "Hasan, Md Zahid and Chen, Jiajing and Wang, Jiyang and Rahman, Mohammed Shaiqur and Joshi, Ameya and Velipasalar, Senem and Hegde, Chinmay and Sharma, Anuj and Sarkar, Soumik",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "Vision-language models can identify distracted driver behavior from naturalistic videos",
    year = "2024"
}

Chen et al., A Driving Risk Assessment Framework Considering Driver’s Fatigue State and Distraction Behavior, Trans. ITS, 2024 | paper

Dataset(s): SFDDD, Dashcam, private

@article{2024_T-ITS_Chen,
    author = "Chen, Jiansong and Zhang, Qixiang and Chen, Jinxin and Wang, Jinxiang and Fang, Zhenwu and Liu, Yahui and Yin, Guodong",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "A Driving Risk Assessment Framework Considering Driver’s Fatigue State and Distraction Behavior",
    year = "2024"
}

Chai et al., Rethinking the Evaluation of Driver Behavior Analysis Approaches, Trans. ITS, 2024 | paper

Dataset(s): SFDDD, AI CITY NDAR

@article{2024_T-ITS_Chai,
    author = "Chai, Weiheng and Wang, Jiyang and Chen, Jiajing and Velipasalar, Senem and Sharma, Anuj",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "Rethinking the Evaluation of Driver Behavior Analysis Approaches",
    year = "2024"
}

Pizarro et al., DRVMon-VM: Distracted driver recognition using large pre-trained video transformers, IV, 2024 | paper

Dataset(s): Drive&Act

@inproceedings{2024_IV_Pizarro,
    author = "Pizarro, Ricardo and Bergasa, Luis M and Baumela, Luis and Buenaposada, Jos{\'e} M and Barea, Rafael",
    booktitle = "2024 IEEE Intelligent Vehicles Symposium (IV)",
    organization = "IEEE",
    pages = "1901--1906",
    title = "DRVMon-VM: Distracted driver recognition using large pre-trained video transformers",
    year = "2024"
}

Palo et al., Holistic Driver Monitoring: A Multi-Task Approach for In-Cabin Driver Attention Evaluation through Multi-Camera Data, IV, 2024 | paper

Dataset(s): DMD

@inproceedings{2024_IV_Palo,
    author = "Palo, Patitapaban and Nayak, Satyajit and Modhugu, Durga Nagendra Raghava Kumar and Gupta, Kwanit and Uttarkabat, Satarupa",
    booktitle = "2024 IEEE Intelligent Vehicles Symposium (IV)",
    organization = "IEEE",
    pages = "1361--1366",
    title = "Holistic Driver Monitoring: A Multi-Task Approach for In-Cabin Driver Attention Evaluation through Multi-Camera Data",
    year = "2024"
}

Ma et al., ViT-DD: Multi-Task Vision Transformer for Semi-Supervised Driver Distraction Detection, IV, 2024 | paper | code

Dataset(s): SFDDD, AUCD2

@inproceedings{2024_IV_Ma,
    author = "Ma, Yunsheng and Wang, Ziran",
    booktitle = "2024 IEEE Intelligent Vehicles Symposium (IV)",
    organization = "IEEE",
    pages = "417--423",
    title = "Vit-dd: Multi-task vision transformer for semi-supervised driver distraction detection",
    year = "2024"
}

Mittal et al., CAT-CapsNet: A Convolutional and Attention Based Capsule Network to Detect the Driver’s Distraction, Trans. ITS, 2023 | paper

Dataset(s): AUCD2, SFDDD

@article{2023_T-ITS_Mittal,
    author = "Mittal, Himanshu and Verma, Bindu",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "CAT-CapsNet: A Convolutional and Attention Based Capsule Network to Detect the Driver’s Distraction",
    year = "2023"
}

Mittal et al., CAT-CapsNet: A Convolutional and Attention Based Capsule Network to Detect the Driver’s Distraction, Trans. ITS, 2023 | paper

Dataset(s): SFDDD, AUCD2

@article{2023_T-ITS_Mittal,
    author = "Mittal, Himanshu and Verma, Bindu",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "CAT-CapsNet: A Convolutional and Attention Based Capsule Network to Detect the Driver’s Distraction",
    year = "2023"
}

Kuang et al., MIFI: MultI-Camera Feature Integration for Robust 3D Distracted Driver Activity Recognition, Trans. ITS, 2023 | paper

Dataset(s): 3MDAD

@article{2023_T-ITS_Kuang,
    author = "Kuang, Jian and Li, Wenjing and Li, Fang and Zhang, Jun and Wu, Zhongcheng",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "MIFI: MultI-Camera Feature Integration for Robust 3D Distracted Driver Activity Recognition",
    year = "2023"
}

Sonth et al., Explainable Driver Activity Recognition Using Video Transformer in Highly Automated Vehicle, IV, 2023 | paper | code

Dataset(s): VTTIMLP01, SHRP2

@inproceedings{2023_IV_Sonth,
    author = "Sonth, Akash and Sarkar, Abhijit and Bhagat, Hirva and Abbott, Lynn",
    booktitle = "2023 IEEE Intelligent Vehicles Symposium (IV)",
    organization = "IEEE",
    pages = "1--8",
    title = "Explainable Driver Activity Recognition Using Video Transformer in Highly Automated Vehicle",
    year = "2023"
}

Morales-Alvarez et al., On Transferability of Driver Observation Models from Simulated to Real Environments in Autonomous Cars, ITSC, 2023 | paper

Dataset(s): Drive&Act, private

@inproceedings{2023_ITSC_Morales-Alvarez,
    author = "Morales-Alvarez, Walter and Certad, Novel and Roitberg, Alina and Stiefelhagen, Rainer and Olaverri-Monreal, Cristina",
    booktitle = "2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)",
    organization = "IEEE",
    pages = "3129--3134",
    title = "On Transferability of Driver Observation Models from Simulated to Real Environments in Autonomous Cars",
    year = "2023"
}

Hamieh et al., Driver Visual Distraction Detection Using Unsupervised Learning Techniques, ITSC, 2023 | paper

Dataset(s): private

@inproceedings{2023_ITSC_Hamieh,
    author = "Hamieh, Salam and Heiries, Vincent and Al-Osman, Hussein and Godin, Christelle and Aloui, Saifeddine",
    booktitle = "2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)",
    organization = "IEEE",
    pages = "945--950",
    title = "Driver Visual Distraction Detection Using Unsupervised Learning Techniques",
    year = "2023"
}

Zhou et al., Multi View Action Recognition for Distracted Driver Behavior Localization, CVPRW, 2023 | paper | code

Dataset(s): AI CITY NDAR

@inproceedings{2023_CVPRW_Zhou,
    author = "Zhou, Wei and Qian, Yinlong and Jie, Zequn and Ma, Lin",
    booktitle = "Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition",
    pages = "5375--5380",
    title = "Multi view action recognition for distracted driver behavior localization",
    year = "2023"
}

Du et al., A Multimodal Fusion Fatigue Driving Detection Method Based on Heart Rate and PERCLOS, Trans. ITS, 2022 | paper

Dataset(s): RLDD

@article{2022_T-ITS_Du,
    author = "Du, Guanglong and Zhang, Linlin and Su, Kang and Wang, Xueqian and Teng, Shaohua and Liu, Peter X",
    journal = "Ieee Transactions on Intelligent Transportation Systems",
    number = "11",
    pages = "21810--21820",
    publisher = "IEEE",
    title = "A multimodal fusion fatigue driving detection method based on heart rate and PERCLOS",
    volume = "23",
    year = "2022"
}

Doshi et al., Federated Learning-based Driver Activity Recognition for Edge Devices, CVPRW, 2022 | paper

Dataset(s): SynDD1

@inproceedings{2022_CVPRW_Doshi,
    author = "Doshi, Keval and Yilmaz, Yasin",
    booktitle = "Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition",
    pages = "3338--3346",
    title = "Federated learning-based driver activity recognition for edge devices",
    year = "2022"
}

Ding et al., A Coarse-to-Fine Boundary Localization method for Naturalistic Driving Action Recognition, CVPRW, 2022 | paper

Dataset(s): SynDD1

@article{2022_CVPRW_Ding,
    author = "Du, Guanglong and Zhang, Linlin and Su, Kang and Wang, Xueqian and Teng, Shaohua and Liu, Peter X",
    journal = "Ieee Transactions on Intelligent Transportation Systems",
    number = "11",
    pages = "21810--21820",
    publisher = "IEEE",
    title = "A multimodal fusion fatigue driving detection method based on heart rate and PERCLOS",
    volume = "23",
    year = "2022"
}

Alyahya et al., Temporal Driver Action Localization using Action Classification Methods, CVPRW, 2022 | paper

Dataset(s): SynDD1

@inproceedings{2022_CVPRW_Alyahya,
    author = "Alyahya, Munirah and Alghannam, Shahad and Alhussan, Taghreed",
    booktitle = "Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition",
    pages = "3319--3326",
    title = "Temporal Driver Action Localization using Action Classification Methods",
    year = "2022"
}

Kopuklu et al., Driver Anomaly Detection: A Dataset and Contrastive Learning Approach, WACV, 2021 | paper

Dataset(s): Dashcam

@inproceedings{2021_WACV_Kopuklu,
    author = "Kopuklu, Okan and Zheng, Jiapeng and Xu, Hang and Rigoll, Gerhard",
    booktitle = "Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision",
    pages = "91--100",
    title = "Driver anomaly detection: A dataset and contrastive learning approach",
    year = "2021"
}

Huang et al., Driver Distraction Detection Based on the True Driver’s Focus of Attention, Trans. ITS, 2021 | paper

Dataset(s): DADA-2000, TrafficSaliency, BDD-A, DR(eye)VE, private

@article{2021_T-ITS_Huang,
    author = "Huang, Jianling and Long, Yan and Zhao, Xiaohua",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "Driver Glance Behavior Modeling Based on Semi-Supervised Clustering and Piecewise Aggregate Representation",
    year = "2021"
}

Chen et al., Fine-Grained Detection of Driver Distraction Based on Neural Architecture Search, Trans. ITS, 2021 | paper

Dataset(s): C42CN

@article{2021_T-ITS_Chen,
    author = "Chen, Jie and Jiang, YaNan and Huang, ZhiXiang and Guo, XiaoHui and Wu, BoCai and Sun, Long and Wu, Tao",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    title = "Fine-Grained Detection of Driver Distraction Based on Neural Architecture Search",
    year = "2021"
}

Yang et al., Recognition of visual-related non-driving activities using a dual-camera monitoring system, PR, 2021 | paper

Dataset(s): private

@article{2021_PR_Yang,
    author = "Yang, Lichao and Dong, Kuo and Ding, Yan and Brighton, James and Zhan, Zhenfei and Zhao, Yifan",
    journal = "Pattern Recognition",
    pages = "107955",
    title = "Recognition of visual-related non-driving activities using a dual-camera monitoring system",
    volume = "116",
    year = "2021"
}

Yang et al., Recognition of visual-related non-driving activities using a dual-camera monitoring system, Pattern Recognition, 2021 | paper

Dataset(s): private

@article{2021_PR_Yang,
    author = "Yang, Lichao and Dong, Kuo and Ding, Yan and Brighton, James and Zhan, Zhenfei and Zhao, Yifan",
    journal = "Pattern Recognition",
    pages = "107955",
    title = "Recognition of visual-related non-driving activities using a dual-camera monitoring system",
    volume = "116",
    year = "2021"
}

Tran et al., Real-time Detection of Distracted Driving using Dual Cameras, IROS, 2020 | paper

Dataset(s): private

@inproceedings{2020_IROS_Tran,
    author = "Tran, Duy and Do, Ha Manh and Lu, Jiaxing and Sheng, Weihua",
    booktitle = "IROS",
    title = "Real-time Detection of Distracted Driving using Dual Cameras",
    year = "2020"
}

Fan et al., GazMon: Eye Gazing Enabled Driving Behavior Monitoring and Prediction, IEEE Transactions on Mobile Computing, 2019 | paper

Dataset(s): private

@article{2019_TMC_Fan,
    author = "Fan, Xiaoyi and Wang, Feng and Song, Danyang and Lu, Yuhe and Liu, Jiangchuan",
    journal = "IEEE Transactions on Mobile Computing",
    title = "{GazMon: Eye Gazing Enabled Driving Behavior Monitoring and Prediction}",
    year = "2019"
}

Chiou et al., Driver Monitoring Using Sparse Representation With Part-Based Temporal Face Descriptors, Trans. ITS, 2019 | paper

Dataset(s): YawDD, NTHU-DDD

@article{2019_T-ITS_Chiou,
    author = "Chiou, Chien-Yu and Wang, Wei-Cheng and Lu, Shueh-Chou and Huang, Chun-Rong and Chung, Pau-Choo and Lai, Yun-Yang",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "1",
    pages = "346--361",
    publisher = "IEEE",
    title = "Driver monitoring using sparse representation with part-based temporal face descriptors",
    volume = "21",
    year = "2019"
}

Wang et al., Real-Time Workload Classification during Driving using HyperNetworks, IROS, 2018 | paper

Dataset(s): private

@inproceedings{2018_IROS_Wang,
    author = "Wang, Ruohan and Amadori, Pierluigi V and Demiris, Yiannis",
    booktitle = "IROS",
    title = "Real-time workload classification during driving using hypernetworks",
    year = "2018"
}

Abouelnaga et al., Real-time Distracted Driver Posture Classification, NeurIPSW, 2018 | paper

Dataset(s): AUCDD

@inproceedings{2017_NeurIPS_Abouelnaga,
    author = "Abouelnaga, Yehya and Eraqi, Hesham M. and Moustafa, Mohamed N.",
    booktitle = "NeurIPS Workshop on Machine Learning for Intelligent Transportation Systems",
    title = "eal-time Distracted Driver Posture Classification",
    year = "2017"
}

Munoz et al., Distinguishing patterns in drivers’ visual attention allocation using Hidden Markov Models, Transportation Research Part F, 2016 | paper

Dataset(s): private

@article{2016_TransRes_Munoz,
    author = "Mu{\\textasciitilde n}oz, Mauricio and Reimer, Bryan and Lee, Joonbum and Mehler, Bruce and Fridman, Lex",
    journal = "Transportation Research Part F: Traffic Psychology and Behaviour",
    pages = "90--103",
    title = "Distinguishing patterns in drivers’ visual attention allocation using Hidden Markov Models",
    volume = "43",
    year = "2016"
}

Liao et al., Detection of Driver Cognitive Distraction: A Comparison Study of Stop-Controlled Intersection and Speed-Limited Highway, Trans. ITS, 2016 | paper

Dataset(s): private

@article{2016_T-ITS_Liao,
    author = "Liao, Yuan and Li, Shengbo Eben and Wang, Wenjun and Wang, Ying and Li, Guofa and Cheng, Bo",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "6",
    pages = "1628--1637",
    publisher = "IEEE",
    title = "Detection of driver cognitive distraction: A comparison study of stop-controlled intersection and speed-limited highway",
    volume = "17",
    year = "2016"
}

Li et al., Detecting Drivers’ Mirror-Checking Actions and Its Application to Maneuver and Secondary Task Recognition, Trans. ITS, 2016 | paper

Dataset(s): private

@article{2016_T-ITS_Li,
    author = "Li, Nanxiang and Busso, Carlos",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "4",
    pages = "980--992",
    publisher = "IEEE",
    title = "Detecting drivers' mirror-checking actions and its application to maneuver and secondary task recognition",
    volume = "17",
    year = "2015"
}

Liao et al., Detection of Driver Cognitive Distraction: A Comparison Study of Stop-Controlled Intersection and Speed-Limited Highway, IV, 2016 | paper

Dataset(s): private

@inproceedings{2016_IV_Liao,
    author = "Liao, Yuan and Li, Shengbo Eben and Li, Guofa and Wang, Wenjun and Cheng, Bo and Chen, Fang",
    booktitle = "IV",
    title = "Detection of driver cognitive distraction: An SVM based real-time algorithm and its comparison study in typical driving scenarios",
    year = "2016"
}

Kim et al., Fusion of Driver-information Based Driver Status Recognition for Co-Pilot System, IV, 2016 | paper

Dataset(s): private

@inproceedings{2016_IV_Kim,
    author = "Kim, Jinwoo and Kim, Kitae and Yoon, Daesub and Koo, Yongbon and Han, Wooyong",
    booktitle = "2016 Ieee Intelligent Vehicles Symposium (iv)",
    organization = "IEEE",
    pages = "1398--1403",
    title = "Fusion of driver-information based driver status recognition for co-pilot system",
    year = "2016"
}

Liu et al., Driver Distraction Detection Using Semi-Supervised Machine Learning, Trans. ITS, 2015 | paper

Dataset(s): private

@article{2015_T-ITS_Liu,
    author = "Liu, Tianchi and Yang, Yan and Huang, Guang-Bin and Yeo, Yong Kiang and Lin, Zhiping",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "4",
    pages = "1108--1120",
    title = "Driver distraction detection using semi-supervised machine learning",
    volume = "17",
    year = "2015"
}

Li et al., Predicting Perceived Visual and Cognitive Distractions of Drivers With Multimodal Features, Trans. ITS, 2015 | paper

Dataset(s): private

@article{2015_T-ITS_Li,
    author = "Li, Nanxiang and Busso, Carlos",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "1",
    pages = "51--65",
    title = "Predicting perceived visual and cognitive distractions of drivers with multimodal features",
    volume = "16",
    year = "2014"
}

Braunagel et al., Driver-Activity Recognition in the Context of Conditionally Autonomous Driving, Trans. ITS, 2015 | paper

Dataset(s): private

@inproceedings{2015_T-ITS_Braunagel,
    author = "Braunagel, Christian and Kasneci, Enkelejda and Stolzmann, Wolfgang and Rosenstiel, Wolfgang",
    booktitle = "ITSC",
    title = "Driver-activity recognition in the context of conditionally autonomous driving",
    year = "2015"
}

Liu et al., Cluster regularized extreme learning machine for detecting mixed-type distraction in driving, ITSC, 2015 | paper

Dataset(s): private

@inproceedings{2015_ITSC_Liu,
    author = "Liu, Tianchi and Yang, Yan and Huang, Guang-Bin and Lin, Zhiping and Klanner, Felix and Denk, Cornelia and Rasshofer, Ralph H",
    booktitle = "ITSC",
    title = "Cluster regularized extreme learning machine for detecting mixed-type distraction in driving",
    year = "2015"
}

Seshadri et al., Driver Cell Phone Usage Detection on Strategic Highway Research Program (SHRP2) Face View Videos, CVPRW, 2015 | paper

Dataset(s): SHRP2

@inproceedings{2015_CVPRW_Seshadri,
    author = "Seshadri, Keshav and Juefei-Xu, Felix and Pal, Dipan K and Savvides, Marios and Thor, Craig P",
    booktitle = "CVPRW",
    title = "Driver cell phone usage detection on strategic highway research program (shrp2) face view videos",
    year = "2015"
}

Hirayama et al., Analysis of Peripheral Vehicular Behavior in Driver’s Gaze Transition: Differences between Driver’s Neutral and Cognitive Distraction States, ITSC, 2014 | paper

Dataset(s): private

@inproceedings{2014_ITSC_Hirayama,
    author = "Hirayama, Takatsugu and Sato, Shota and Mase, Kenji and Miyajima, Chiyomi and Takeda, Kazuya",
    booktitle = "ITSC",
    title = "Analysis of peripheral vehicular behavior in driver's gaze transition: Differences between driver's neutral and cognitive distraction states",
    year = "2014"
}

Tango et al., Real-Time Detection System of Driver Distraction Using Machine Learning, Trans. ITS, 2013 | paper

Dataset(s): private

@article{2013_T-ITS_Tango,
    author = "Tango, Fabio and Botta, Marco",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "2",
    pages = "894--905",
    title = "Real-time detection system of driver distraction using machine learning",
    volume = "14",
    year = "2013"
}

Mbouna et al., Visual Analysis of Eye State and Head Pose for Driver Alertness Monitoring, Trans. ITS, 2013 | paper

Dataset(s): BU HeadTracking, private

@article{2013_T-ITS_Mbouna,
    author = "Mbouna, Ralph Oyini and Kong, Seong G and Chun, Myung-Geun",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "3",
    pages = "1462--1469",
    title = "Visual analysis of eye state and head pose for driver alertness monitoring",
    volume = "14",
    year = "2013"
}

Masala et al., Detecting Driver Inattention by Rough Iconic Classification, IV, 2013 | paper

Dataset(s): private

@inproceedings{2013_IV_Masala,
    author = "Masala, Giovanni Luca and Grosso, Enrico",
    booktitle = "2013 IEEE Intelligent Vehicles Symposium (IV)",
    organization = "IEEE",
    pages = "913--918",
    title = "Detecting driver inattention by rough iconic classification",
    year = "2013"
}

Ahlstrom et al., A Gaze-Based Driver Distraction Warning System and Its Effect on Visual Behavior, Driver Distraction and Inattention, 2013 | paper

Dataset(s): private

@inbook{2013_DDI_Ahlstrom,
    author = "Kircher, Katja and Ahlstrom, Christer",
    editor = "Regan, Michael and Victor, Trent and Lee, John",
    chapter = "The Driver Distraction Detection Algorithm AttenD",
    pages = "327-348",
    publisher = "Ashgate Publishing Ltd.",
    title = "Driver Distraction and Inattention: Advances in Research and Countermeasures, Volume 1",
    year = "2013"
}

Hirayama et al., Detection of Driver Distraction based on Temporal Relationship between Eye-Gaze and Peripheral Vehicle Behavior, ITSC, 2012 | paper

Dataset(s): private

@inproceedings{2012_ITSC_Hirayama,
    author = "Hirayama, Takatsugu and Mase, Kenji and Takeda, Kazuya",
    booktitle = "ITSC",
    title = "Detection of driver distraction based on temporal relationship between eye-gaze and peripheral vehicle behavior",
    year = "2012"
}

Wollmer et al., Online Driver Distraction Detection UsingLong Short-Term Memory, Trans. ITS, 2011 | paper

Dataset(s): private

@article{2011_T-ITS_Wollmer,
    author = {Wollmer, Martin and Blaschke, Christoph and Schindl, Thomas and Schuller, Bj{\"o}rn and Farber, Berthold and Mayer, Stefan and Trefflich, Benjamin},
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "2",
    pages = "574--582",
    title = "Online driver distraction detection using long short-term memory",
    volume = "12",
    year = "2011"
}

Jo et al., Vision-based method for detecting driver drowsiness and distraction in driver monitoring system, Optical Engineering, 2011 | paper

Dataset(s): private

@article{2011_OptEng_Jo,
    author = "Jo, Jaeik and Lee, Sung Joo and Kim, Jaihie and Jung, Ho Gi and Park, Kang Ryoung",
    journal = "Optical Engineering",
    number = "12",
    pages = "127202",
    title = "Vision-based method for detecting driver drowsiness and distraction in driver monitoring system",
    volume = "50",
    year = "2011"
}

Flores et al., Driver drowsiness detection system under infrared illumination for an intelligent vehicle, IET Intelligent Transport Systems, 2011 | paper

Dataset(s): private

@article{2011_IET_Flores,
    author = "Flores, Marco Javier and Armingol, J Ma and de la Escalera, Arturo",
    journal = "IET Intelligent Transport Systems",
    number = "4",
    pages = "241--251",
    publisher = "IET",
    title = "Driver drowsiness detection system under infrared illumination for an intelligent vehicle",
    volume = "5",
    year = "2011"
}