scene_gaze.md

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Home  | Behavioral  | Applications  | Datasets  

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., Context-Aware Driver Attention Estimation Using Multi-Hierarchy Saliency Fusion With Gaze Tracking, Trans. ITS, 2024 | paper

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

@article{2024_T-ITS_Hu,
    author = "Hu, Zhongxu and Cai, Yuxin and Li, Qinghua and Su, Kui and Lv, Chen",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "Context-Aware Driver Attention Estimation Using Multi-Hierarchy Saliency Fusion With Gaze Tracking",
    year = "2024"
}

Kotseruba et al., SCOUT+: Towards Practical Task-Driven Drivers’ Gaze Prediction, IV, 2024 | paper | code

Dataset(s): DR(eye)VE, BDD-A, SCOUT

@inproceedings{2024_IV_Kotseruba_2,
    author = "Kotseruba, Iuliia and Tsotsos, John K",
    booktitle = "Intelligent Vehicles Symposium (IV)",
    title = "{SCOUT+: Towards Practical Task-Driven Drivers' Gaze Prediction}",
    year = "2024"
}

Kotseruba et al., Data Limitations for Modeling Top-Down Effects on Drivers’ Attention, IV, 2024 | paper | code

Dataset(s): DR(eye)VE, BDD-A, MAAD, LBW, SCOUT

@inproceedings{2024_IV_Kotseruba_1,
    author = "Kotseruba, Iuliia and Tsotsos, John K",
    booktitle = "Intelligent Vehicles Symposium (IV)",
    title = "Data Limitations for Modeling Top-Down Effects on Drivers' Attention",
    year = "2024"
}

Kotseruba et al., Understanding and Modeling the Effects of Task and Context on Drivers’ Gaze Allocation, IV, 2024 | paper | code

Dataset(s): DR(eye)VE, SCOUT

@inproceedings{2024_IV_Kotseruba,
    author = "Kotseruba, Iuliia and Tsotsos, John K",
    booktitle = "2024 IEEE Intelligent Vehicles Symposium (IV)",
    organization = "IEEE",
    pages = "1337--1344",
    title = "Understanding and modeling the effects of task and context on drivers’ gaze allocation",
    year = "2024"
}

Greer et al., Robust Traffic Light Detection Using Salience-Sensitive Loss: Computational Framework and Evaluations, IV, 2024 | paper

Dataset(s): private

@inproceedings{2024_IV_Greer,
    author = "Greer, Ross and Gopalkrishnan, Akshay and Landgren, Jacob and Rakla, Lulua and Gopalan, Anish and Trivedi, Mohan",
    booktitle = "2023 IEEE Intelligent Vehicles Symposium (IV)",
    organization = "IEEE",
    pages = "1--7",
    title = "Robust traffic light detection using salience-sensitive loss: Computational framework and evaluations",
    year = "2023"
}

Adhikari et al., Comparative Study of Attention among Drivers with Varying Driving Experience, IV, 2024 | paper

Dataset(s): BDD-A, private

@inproceedings{2024_IV_Adhikari,
    author = "Adhikari, Bikram and Duri{\'c}, Zoran and Wijesekera, Duminda and Yu, Bo",
    booktitle = "2024 IEEE Intelligent Vehicles Symposium (IV)",
    organization = "IEEE",
    pages = "1353--1360",
    title = "Comparative Study of Attention among Drivers with Varying Driving Experience",
    year = "2024"
}

Jia et al., TFGNet: Traffic Salient Object Detection Using a Feature Deep Interaction and Guidance Fusion, Trans. ITS, 2023 | paper

Dataset(s): DUTS, DUT-OMRON, ECSSD, HKU-IS, SOD, PASCAL-S, TSOD

@article{2023_T-ITS_Jia,
    author = "Jia, Ning and Sun, Yougang and Liu, Xianhui",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "TFGNet: Traffic salient object detection using a feature deep interaction and guidance fusion",
    year = "2023"
}

Deng et al., Driving Visual Saliency Prediction of Dynamic Night Scenes via a Spatio-Temporal Dual-Encoder Network, Trans. ITS, 2023 | paper | code

Dataset(s): DrFixD-night, DR(eye)VE

@article{2023_T-ITS_Deng,
    author = "Deng, Tao and Jiang, Lianfang and Shi, Yi and Wu, Jiang and Wu, Zhangbi and Yan, Shun and Zhang, Xianshi and Yan, Hongmei",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    publisher = "IEEE",
    title = "Driving Visual Saliency Prediction of Dynamic Night Scenes via a Spatio-Temporal Dual-Encoder Network",
    year = "2023"
}

Biswas et al., Characterizing Drivers’ Peripheral Vision via the Functional Field of View for Intelligent Driving Assistance, IV, 2023 | paper

Dataset(s): private

@inproceedings{2023_IV_Biswas,
    author = "Biswas, Abhijat and Admoni, Henny",
    booktitle = "2023 IEEE Intelligent Vehicles Symposium (IV)",
    organization = "IEEE",
    pages = "1--8",
    title = "Characterizing Drivers’ Peripheral Vision via the Functional Field of View for Intelligent Driving Assistance",
    year = "2023"
}

Bhagat et al., Driver Gaze Fixation and Pattern Analysis in Safety Critical Events, IV, 2023 | paper | code

Dataset(s): SHRP2

@inproceedings{2023_IV_Bhagat,
    author = "Bhagat, Hirva and Jain, Sandesh and Abbott, Lynn and Sonth, Akash and Sarkar, Abhijit",
    booktitle = "2023 IEEE Intelligent Vehicles Symposium (IV)",
    organization = "IEEE",
    pages = "1--8",
    title = "Driver gaze fixation and pattern analysis in safety critical events",
    year = "2023"
}

Zhao et al., Gated Driver Attention Predictor, ITSC, 2023 | paper | code

Dataset(s): DADA-2000, BDD-A

@inproceedings{2023_ITSC_Zhao,
    author = "Zhao, Tianci and Bai, Xue and Fang, Jianwu and Xue, Jianru",
    booktitle = "2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)",
    organization = "IEEE",
    pages = "270--276",
    title = "Gated Driver Attention Predictor",
    year = "2023"
}

Bao et al., Personalized Causal Factor Generalization for Subjective Risky Scene Understanding with Vision Transforme, ITSC, 2023 | paper

Dataset(s): private

@inproceedings{2023_ITSC_Bao,
    author = "Bao, Naren and Carballo, Alexander and Tsukada, Manabu and Takeda, Kazuya",
    booktitle = "2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)",
    organization = "IEEE",
    pages = "4637--4643",
    title = "Personalized Causal Factor Generalization for Subjective Risky Scene Understanding with Vision Transformer",
    year = "2023"
}

Zhu et al., Unsupervised Self-Driving Attention Prediction via Uncertainty Mining and Knowledge Embedding, ICCV, 2023 | paper | code

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

@inproceedings{2023_ICCV_Zhu,
    author = "Zhu, Pengfei and Qi, Mengshi and Li, Xia and Li, Weijian and Ma, Huadong",
    booktitle = "Proceedings of the IEEE/CVF International Conference on Computer Vision",
    pages = "8558--8568",
    title = "Unsupervised self-driving attention prediction via uncertainty mining and knowledge embedding",
    year = "2023"
}

Chen et al., FBLNet: FeedBack Loop Network for Driver Attention Prediction, ICCV, 2023 | paper

Dataset(s): BDD-A, DADA-2000

@inproceedings{2023_ICCV_Chen,
    author = "Chen, Yilong and Nan, Zhixiong and Xiang, Tao",
    booktitle = "Proceedings of the IEEE/CVF International Conference on Computer Vision",
    pages = "13371--13380",
    title = "FBLNet: FeedBack Loop Network for Driver Attention Prediction",
    year = "2023"
}

Qin et al., ID-YOLO: Real-Time Salient Object Detection Based on the Driver’s Fixation Region, Trans. ITS, 2022 | paper

Dataset(s): private

@article{2022_T-ITS_Qin,
    author = "Qin, Long and Shi, Yi and He, Yahui and Zhang, Junrui and Zhang, Xianshi and Li, Yongjie and Deng, Tao and Yan, Hongmei",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "9",
    pages = "15898--15908",
    publisher = "IEEE",
    title = "ID-YOLO: Real-time salient object detection based on the driver’s fixation region",
    volume = "23",
    year = "2022"
}

Li et al., Adaptive Short-Temporal Induced Aware Fusion Network for Predicting Attention Regions Like a Driver, Trans. ITS, 2022 | paper | code

Dataset(s): BDD-A, DADA-2000, TrafficSaliency

@article{2022_T-ITS_Li,
    author = "Li, Qiang and Liu, Chunsheng and Chang, Faliang and Li, Shuang and Liu, Hui and Liu, Zehao",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "10",
    pages = "18695--18706",
    publisher = "IEEE",
    title = "Adaptive short-temporal induced aware fusion network for predicting attention regions like a driver",
    volume = "23",
    year = "2022"
}

Gan et al., Multisource Adaption for Driver Attention Prediction in Arbitrary Driving Scenes, Trans. ITS, 2022 | paper

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

@article{2022_T-ITS_Gan,
    author = "Gan, Shun and Pei, Xizhe and Ge, Yulong and Wang, Qingfan and Shang, Shi and Li, Shengbo Eben and Nie, Bingbing",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "11",
    pages = "20912--20925",
    publisher = "IEEE",
    title = "Multisource Adaption for Driver Attention Prediction in Arbitrary Driving Scenes",
    volume = "23",
    year = "2022"
}

Fang et al., DADA: Driver Attention Prediction in Driving Accident Scenarios, Trans. ITS, 2021 | paper | code

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

@article{2022_T-ITS_Fang,
    author = "Fang, Jianwu and Yan, Dingxin and Qiao, Jiahuan and Xue, Jianru and Yu, Hongkai",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "6",
    pages = "4959--4971",
    publisher = "IEEE",
    title = "DADA: Driver attention prediction in driving accident scenarios",
    volume = "23",
    year = "2021"
}

Araluce et al., ARAGAN: A dRiver Attention estimation model based on conditional Generative Adversarial Network, IV, 2022 | paper | code

Dataset(s): BDD-A, DADA-2000

@inproceedings{2022_IV_Araluce,
    author = "Araluce, Javier and Bergasa, Luis M and Oca{\\textasciitilde n}a, Manuel and Barea, Rafael and L{\'o}pez-Guill{\'e}n, Elena and Revenga, Pedro",
    booktitle = "2022 IEEE Intelligent Vehicles Symposium (IV)",
    organization = "IEEE",
    pages = "1066--1072",
    title = "ARAGAN: A dRiver Attention estimation model based on conditional Generative Adversarial Network",
    year = "2022"
}

Kasahara et al., Look Both Ways: Self-Supervising Driver Gaze Estimation and Road Scene Saliency, ECCV, 2022 | paper | code

Dataset(s): LBW

@inproceedings{2022_ECCV_Kasahara,
    author = "Kasahara, Isaac and Stent, Simon and Park, Hyun Soo",
    booktitle = "Computer Vision--ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23--27, 2022, Proceedings, Part XIII",
    organization = "Springer",
    pages = "126--142",
    title = "Look Both Ways: Self-supervising Driver Gaze Estimation and Road Scene Saliency",
    year = "2022"
}

Amadori et al., HammerDrive: A Task-Aware Driving Visual Attention Model, Trans. ITS, 2021 | paper

Dataset(s): private

@article{2021_T-ITS_Amadori,
    author = "Amadori, Pierluigi Vito and Fischer, Tobias and Demiris, Yiannis",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    title = "HammerDrive: A Task-Aware Driving Visual Attention Model",
    year = "2021"
}

Epple et al., How Do Drivers Observe Surrounding Vehicles in Real-World Traffic? Estimating the Drivers Primary Observed Traffic Objects, IV, 2021 | paper

Dataset(s): private

@inproceedings{2021_IV_Epple,
    author = "Epple, Nico and Chopra, Harshit and Riener, Andreas",
    booktitle = "2021 IEEE Intelligent Vehicles Symposium (IV)",
    organization = "IEEE",
    pages = "594--601",
    title = "How Do Drivers Observe Surrounding Vehicles in Real-World Traffic? Estimating the Drivers Primary Observed Traffic Objects",
    year = "2021"
}

Gopinath et al., MAAD: A Model and Dataset for “Attended Awareness” in Driving, ICCVW, 2021 | paper | code

Dataset(s): MAAD

@inproceedings{2021_ICCVW_Gopinath,
    author = "Gopinath, Deepak and Rosman, Guy and Stent, Simon and Terahata, Katsuya and Fletcher, Luke and Argall, Brenna and Leonard, John",
    booktitle = "Proceedings of the IEEE/CVF International Conference on Computer Vision",
    pages = "3426--3436",
    title = {MAAD: A Model and Dataset for" Attended Awareness" in Driving},
    year = "2021"
}

Baee et al., MEDIRL: Predicting the Visual Attention of Drivers via Maximum Entropy Deep Inverse Reinforcement Learning, ICCV, 2021 | paper | code

Dataset(s): Eyecar

@inproceedings{2021_ICCV_Baee,
    author = "Baee, Sonia and Pakdamanian, Erfan and Kim, Inki and Feng, Lu and Ordonez, Vicente and Barnes, Laura",
    booktitle = "ICCV",
    title = "MEDIRL: Predicting the visual attention of drivers via maximum entropy deep inverse reinforcement learning",
    year = "2021"
}

Deng et al., How Do Drivers Allocate Their Potential Attention? Driving Fixation Prediction via Convolutional Neural Networks, Trans. ITS, 2020 | paper | code

Dataset(s): TrafficSaliency

@article{2020_T-ITS_Deng,
    author = "Deng, Tao and Yan, Hongmei and Qin, Long and Ngo, Thuyen and Manjunath, BS",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "5",
    pages = "2146--2154",
    publisher = "IEEE",
    title = "{How do drivers allocate their potential attention? Driving fixation prediction via convolutional neural networks}",
    volume = "21",
    year = "2019"
}

Zhang et al., Interaction Graphs for Object Importance Estimation in On-road Driving Videos, ICRA, 2020 | paper

Dataset(s): private

@inproceedings{2020_ICRA_Zhang,
    author = "Zhang, Zehua and Tawari, Ashish and Martin, Sujitha and Crandall, David",
    booktitle = "ICRA",
    title = "Interaction Graphs for Object Importance Estimation in On-road Driving Videos",
    year = "2020"
}

Pal et al., “Looking at the right stuff” - Guided semantic-gaze for autonomous driving, CVPR, 2020 | paper | code

Dataset(s): DR(eye)VE, BDD-A, JAAD

@inproceedings{2020_CVPR_Pal,
    author = "Pal, Anwesan and Mondal, Sayan and Christensen, Henrik I",
    booktitle = "CVPR",
    title = {{" Looking at the Right Stuff"-Guided Semantic-Gaze for Autonomous Driving}},
    year = "2020"
}

Tavakoli et al., Digging Deeper into Egocentric Gaze Prediction, WACV, 2019 | paper

Dataset(s): 3DDS

@inproceedings{2019_WACV_Tavakoli,
    author = "Tavakoli, Hamed Rezazadegan and Rahtu, Esa and Kannala, Juho and Borji, Ali",
    booktitle = "WACV",
    title = "Digging deeper into egocentric gaze prediction",
    year = "2019"
}

Rahimpour et al., Context Aware Road-user Importance Estimation (iCARE), IV, 2019 | paper

Dataset(s): private

@inproceedings{2019_IV_Rahimpour,
    author = "Rahimpour, Alireza and Martin, Sujitha and Tawari, Ashish and Qi, Hairong",
    booktitle = "IV",
    title = "{Context Aware Road-user Importance Estimation (iCARE)}",
    year = "2019"
}

Ning et al., An Efficient Model for Driving Focus of Attention Prediction using Deep Learning, ITSC, 2019 | paper

Dataset(s): DR(eye)VE

@inproceedings{2019_ITSC_Ning,
    author = "Ning, Minghao and Lu, Chao and Gong, Jianwei",
    booktitle = "ITCS",
    title = "{An Efficient Model for Driving Focus of Attention Prediction using Deep Learning}",
    year = "2019"
}

Gao et al., Goal-oriented object importance estimation in on-road driving videos, ICRA, 2019 | paper

Dataset(s): private

@inproceedings{2019_ICRA_Gao,
    author = "Gao, Mingfei and Tawari, Ashish and Martin, Sujitha",
    booktitle = "ICRA",
    title = "Goal-oriented object importance estimation in on-road driving videos",
    year = "2019"
}

Palasek et al., Attentional demand estimation with attentive driving models, BMVC, 2019 | paper

Dataset(s): private

@inproceedings{2019_BMVC_Palasek,
    author = "Palasek, Petar and Lavie, Nilli and Palmer, Luke",
    booktitle = "BMVC",
    title = "Attentional demand estimation with attentive driving models",
    year = "2019"
}

Deng et al., Learning to Boost Bottom-Up Fixation Prediction in Driving Environments via Random Forest, Trans. ITS, 2018 | paper

Dataset(s): TETD

@article{2018_T-ITS_Deng,
    author = "Deng, Tao and Yan, Hongmei and Li, Yong-Jie",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "9",
    pages = "3059--3067",
    title = "Learning to boost bottom-up fixation prediction in driving environments via random forest",
    volume = "19",
    year = "2017"
}

Palazzi et al., Predicting the Driver’s Focus of Attention: the DR(eye)VE Project, PAMI, 2018 | paper | code

Dataset(s): DR(eye)VE

@article{2018_PAMI_Palazzi,
    author = "Palazzi, Andrea and Abati, Davide and Solera, Francesco and Cucchiara, Rita and others",
    journal = "IEEE TPAMI",
    number = "7",
    pages = "1720--1733",
    title = "{Predicting the Driver's Focus of Attention: the DR (eye) VE Project}",
    volume = "41",
    year = "2018"
}

Tawari et al., Learning to Attend to Salient Targets in Driving Videos Using Fully Convolutional RNN, ITSC, 2018 | paper

Dataset(s): private

@inproceedings{2018_ITSC_Tawari,
    author = "Tawari, Ashish and Mallela, Praneeta and Martin, Sujitha",
    booktitle = "ITSC",
    title = "Learning to attend to salient targets in driving videos using fully convolutional rnn",
    year = "2018"
}

Xia et al., Predicting Driver Attention in Critical Situations, ACCV, 2018 | paper | code

Dataset(s): BDD-A

@inproceedings{2018_ACCV_Xia,
    author = "Xia, Ye and Zhang, Danqing and Kim, Jinkyu and Nakayama, Ken and Zipser, Karl and Whitney, David",
    booktitle = "ACCV",
    title = "Predicting driver attention in critical situations",
    year = "2018"
}

Palmer et al., Predicting the Perceptual Demands of Urban Driving with Video Regression, WACV, 2017 | paper

Dataset(s): private

@inproceedings{2017_WACV_Palmer,
    author = "Palmer, Luke and Bialkowski, Alina and Brostow, Gabriel J and Ambeck-Madsen, Jonas and Lavie, Nilli",
    booktitle = "WACV",
    title = "Predicting the perceptual demands of urban driving with video regression",
    year = "2017"
}

Ohn-Bar et al., Are all objects equal? Deep spatio-temporal importance prediction in driving videos, Pattern Recognition, 2017 | paper | code

Dataset(s): KITTI

@article{2017_PR_Ohn-Bar,
    author = "Ohn-Bar, Eshed and Trivedi, Mohan Manubhai",
    journal = "Pattern Recognition",
    pages = "425--436",
    title = "Are all objects equal? Deep spatio-temporal importance prediction in driving videos",
    volume = "64",
    year = "2017"
}

Tawari et al., A Computational Framework for Driver’s Visual Attention Using A Fully Convolutional Architecture, IV, 2017 | paper

Dataset(s): DR(eye)VE

@inproceedings{2017_IV_Tawari,
    author = "Tawari, Ashish and Kang, Byeongkeun",
    booktitle = "IV",
    title = "A computational framework for driver's visual attention using a fully convolutional architecture",
    year = "2017"
}

Palazzi et al., Learning Where to Attend Like a Human Driver, IV, 2017 | paper | code

Dataset(s): DR(eye)VE

@inproceedings{2017_IV_Palazzi,
    author = "Palazzi, Andrea and Solera, Francesco and Calderara, Simone and Alletto, Stefano and Cucchiara, Rita",
    booktitle = "IV",
    title = "Learning where to attend like a human driver",
    year = "2017"
}

Deng et al., Where Does the Driver Look? Top-Down-Based Saliency Detection in a Traffic Driving Environment, Trans. ITS, 2016 | paper | code

Dataset(s): private

@article{2016_T-ITS_Deng,
    author = "Deng, Tao and Yang, Kaifu and Li, Yongjie and Yan, Hongmei",
    journal = "IEEE Transactions on Intelligent Transportation Systems",
    number = "7",
    pages = "2051--2062",
    publisher = "IEEE",
    title = "Where does the driver look? Top-down-based saliency detection in a traffic driving environment",
    volume = "17",
    year = "2016"
}

Borji et al., What/Where to Look Next? Modeling Top-Down Visual Attention in Complex Interactive Environments, Transactions on Systems, Man, and Cybernetics Systems, 2014 | paper

Dataset(s): 3DDS

@article{2014_TransSysManCybernetics_Borji,
    author = "Borji, Ali and Sihite, Dicky N and Itti, Laurent",
    journal = "IEEE Transactions on Systems, Man, and Cybernetics: Systems",
    number = "5",
    pages = "523--538",
    title = "{What/where to look next? Modeling top-down visual attention in complex interactive environments}",
    volume = "44",
    year = "2013"
}

Johnson et al., Predicting human visuomotor behaviour in a driving task, Philosophical Transactions of the Royal Society: B, 2013 | paper | code

Dataset(s): private

@article{2013_RSTB_Johnson,
    author = "Johnson, Leif and Sullivan, Brian and Hayhoe, Mary and Ballard, Dana",
    journal = "Philosophical Transactions of the Royal Society B: Biological Sciences",
    number = "1636",
    pages = "20130044",
    title = "Predicting human visuomotor behaviour in a driving task",
    volume = "369",
    year = "2014"
}

Borji et al., Probabilistic Learning of Task-Specific Visual Attention, CVPR, 2012 | paper | code

Dataset(s): 3DDS

@inproceedings{2012_CVPR_Borji,
    author = "Borji, Ali and Sihite, Dicky N and Itti, Laurent",
    booktitle = "CVPR",
    title = "Probabilistic learning of task-specific visual attention",
    year = "2012"
}

Borji et al., Computational Modeling of Top-down Visual Attention in Interactive Environments, BMVC, 2011 | paper

Dataset(s): 3DDS

@inproceedings{2011_BMVC_Borji,
    author = "Borji, Ali and Sihite, Dicky N and Itti, Laurent",
    booktitle = "BMVC",
    title = "Computational Modeling of Top-down Visual Attention in Interactive Environments.",
    year = "2011"
}