{"type":"ScholarlyArticle","title":"Human Gaze Assisted Artificial Intelligence: A Review","authors":[{"name":"Ruohan Zhang","slug":"ruohan-zhang","given":"Ruohan","family":"Zhang","affiliation":"The University of Texas at Austin"},{"name":"Akanksha Saran","slug":"akanksha-saran","given":"Akanksha","family":"Saran","affiliation":"The University of Texas at Austin"},{"name":"Bo Liu","slug":"bo-liu","given":"Bo","family":"Liu","affiliation":"The University of Texas at Austin"},{"name":"Yifeng Zhu","slug":"yifeng-zhu","given":"Yifeng","family":"Zhu","affiliation":"The University of Texas at Austin"},{"name":"Sihang Guo","slug":"sihang-guo","given":"Sihang","family":"Guo","affiliation":"The University of Texas at Austin"},{"name":"Scott Niekum","slug":"scott-niekum","given":"Scott","family":"Niekum","affiliation":"The University of Texas at Austin"},{"name":"Dana Ballard","slug":"dana-ballard","given":"Dana","family":"Ballard","affiliation":"The University of Texas at Austin"},{"name":"Mary Hayhoe","slug":"mary-hayhoe","given":"Mary","family":"Hayhoe","affiliation":"The University of Texas at Austin"}],"abstract":"Human gaze reveals a wealth of information about internal cognitive state. Thus, gaze-related research has significantly increased in computer vision, natural language processing, decision learning, and robotics in recent years. We provide a high-level overview of the research efforts in these fields, including collecting human gaze data sets, modeling gaze behaviors, and utilizing gaze information in various applications, with the goal of enhancing communication between these research areas. We discuss future challenges and potential applications that work towards a common goal of human-centered artificial intelligence.","doi":"10.24963/ijcai.2020/689","url":"https://ijcai.org/proceedings/2020/689","pdf":"https://ijcai.org/proceedings/2020/0689.pdf","markdown":"https://ijcai.org/proceedings/2020/689.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/689","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Survey track","track":"Survey track","number":689,"pages":{"first":4951,"last":4958},"keywords":["Vision: general","Human aspects in AI: general","Machine Learning: general"],"videos":[],"references":[{"position":1,"raw":"[Admoni and Scassellati, 2017] Henny Admoni and Brian Scassel- lati. Social eye gaze in human-robot interaction: a review. Jour- nal of Human-Robot Interaction, 6(1):25-63, 2017.","title":"Henny Admoni and Brian Scassellati. Social eye gaze in human-robot interaction: a review","authors":"Scassellati Admoni","year":"2017","venue":"Journal of Human-Robot Interaction","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Admoni et al., 2014] Henny Admoni, Anca Dragan, Siddhartha S Srinivasa, and Brian Scassellati. Deliberate delays during robot- to-human handovers improve compliance with gaze communica- tion. In Proceedings of the 2014 ACM/IEEE international con- ference on Human-robot interaction, pages 49-56, 2014.","title":"Deliberate delays during robotto-human handovers improve compliance with gaze communication","authors":"Henny Admoni, Anca Dragan, Siddhartha S Srinivasa, Brian Scassellati","year":"2014","venue":"Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Admoni et al., 2016] Henny Admoni, Thomas Weng, and Brian Scassellati. Modeling communicative behaviors for object ref- erences in human-robot interaction. In 2016 IEEE International Conference on Robotics and Automation (ICRA), pages 3352- 3359. IEEE, 2016.","title":"Modeling communicative behaviors for object references in human-robot interaction","authors":"Henny Admoni, Thomas Weng, Brian Scassellati","year":"2016","venue":"IEEE International Conference on Robotics and Automation (ICRA)","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Amos et al., 2016] Brandon Amos, Bartosz Ludwiczuk, and Ma- hadev Satyanarayanan. Openface: A general-purpose face recog- nition library with mobile applications. 2016.","title":"Openface: A general-purpose face recognition library with mobile applications","authors":"Brandon Amos, Bartosz Ludwiczuk, Mahadev Satyanarayanan","year":"2016","venue":null,"doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Andrist et al., 2014] Sean Andrist, Xiang Zhi Tan, Michael Gle- icher, and Bilge Mutlu. Conversational gaze aversion for human- like robots. In 2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pages 25-32. IEEE, 2014.","title":"Conversational gaze aversion for humanlike robots","authors":"Sean Andrist, Xiang Zhi Tan, Michael Gleicher, Bilge Mutlu","year":"2014","venue":"2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI)","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Andrist et al., 2017] Sean Andrist, Michael Gleicher, and Bilge Mutlu. Looking coordinated: Bidirectional gaze mechanisms for collaborative interaction with virtual characters. In Proceedings of the 2017 CHI conference on human factors in computing sys- tems, pages 2571-2582, 2017.","title":"Looking coordinated: Bidirectional gaze mechanisms for collaborative interaction with virtual characters","authors":"Sean Andrist, Michael Gleicher, Bilge Mutlu","year":"2017","venue":"Proceedings of the 2017 CHI conference on human factors in computing systems","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Argall et al., 2009] Brenna D Argall, Sonia Chernova, Manuela Veloso, and Brett Browning. A survey of robot learning from demonstration. Robotics and autonomous systems, 57(5):469- 483, 2009.","title":"A survey of robot learning from demonstration","authors":"Sonia Brenna D Argall, Manuela Chernova, Brett Veloso, Browning","year":"2009","venue":"Robotics and autonomous systems","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Aronson et al., 2018] Reuben M Aronson, Thiago Santini, Thomas C Kübler, Enkelejda Kasneci, Siddhartha Srinivasa, and Henny Admoni. Eye-hand behavior in human-robot shared ma- nipulation. In Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction, pages 4-13, 2018.","title":"Eye-hand behavior in human-robot shared manipulation","authors":"Thiago Reuben M Aronson, Santini, C Thomas, Enkelejda Kübler, Siddhartha Kasneci, Henny Srinivasa, Admoni","year":"2018","venue":"Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Balajee Vasudevan et al., 2018] Arun Balajee Vasudevan, Dengxin Dai, and Luc Van Gool. Object referring in videos with language and human gaze. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 4129-4138, 2018.","title":"Object referring in videos with language and human gaze","authors":"Arun Balajee Vasudevan, Dengxin Dai, Luc Van Gool","year":"2018","venue":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Betke, 2010] Margrit Betke. Intelligent interfaces to empower peo- ple with disabilities. In Handbook of Ambient Intelligence and Smart Environments, pages 409-432. Springer, 2010.","title":"Intelligent interfaces to empower people with disabilities","authors":"Margrit Betke","year":"2010","venue":"Handbook of Ambient Intelligence and Smart Environments","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Borji and Itti, 2014] Ali Borji and Laurent Itti. Defending yarbus: Eye movements reveal observers' task. Journal of vision, 14(3):29-29, 2014.","title":"Ali Borji and Laurent Itti. Defending yarbus: Eye movements reveal observers' task","authors":"Itti Borji","year":"2014","venue":"Journal of vision","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Borji et al., 2015] Ali Borji, Ming-Ming Cheng, Huaizu Jiang, and Jia Li. Salient object detection: A benchmark. IEEE transactions on image processing, 24(12):5706-5722, 2015.","title":"Salient object detection: A benchmark","authors":"Ali Borji, Ming-Ming Cheng, Huaizu Jiang, Jia Li","year":"2015","venue":"IEEE transactions on image processing","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Brooks and Meltzoff, 2005] Rechele Brooks and Andrew N Melt- zoff. The development of gaze following and its relation to lan- guage. Developmental science, 8(6):535-543, 2005.","title":"Rechele Brooks and Andrew N Meltzoff. The development of gaze following and its relation to language","authors":"Meltzoff Brooks","year":"2005","venue":"Developmental science","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Bylinskii et al., 2015a] Zoya Bylinskii, Phillip Isola, Constance Bainbridge, Antonio Torralba, and Aude Oliva. Intrinsic and ex- trinsic effects on image memorability. Vision research, 116:165- 178, 2015.","title":"Intrinsic and extrinsic effects on image memorability","authors":"Bylinskii","year":"2015","venue":"Vision research","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Bylinskii et al., 2015b] Zoya Bylinskii, Tilke Judd, Ali Borji, Lau- rent Itti, Frédo Durand, Aude Oliva, and Antonio Torralba. Mit saliency benchmark, 2015.","title":"Mit saliency benchmark","authors":"Bylinskii","year":"2015","venue":null,"doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Bylinskii et al., 2016] Zoya Bylinskii, Adrià Recasens, Ali Borji, Aude Oliva, Antonio Torralba, and Frédo Durand. Where should saliency models look next? In European Conference on Com- puter Vision, pages 809-824. Springer, 2016.","title":"Where should saliency models look next?","authors":"Zoya Bylinskii, Adrià Recasens, Ali Borji, Aude Oliva, Antonio Torralba, Frédo Durand","year":"2016","venue":"European Conference on Computer Vision","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Bylinskii et al., 2019] Zoya Bylinskii, Tilke Judd, Aude Oliva, Antonio Torralba, and Frédo Durand. What do different evalua- tion metrics tell us about saliency models? IEEE transactions on pattern analysis and machine intelligence, 41(3):740-757, 2019.","title":"What do different evaluation metrics tell us about saliency models?","authors":"Zoya Bylinskii, Tilke Judd, Aude Oliva, Antonio Torralba, Frédo Durand","year":"2019","venue":"IEEE transactions on pattern analysis and machine intelligence","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Chen and Zhao, 2018] Shi Chen and Qi Zhao. Boosted attention: Leveraging human attention for image captioning. In Proceed- ings of the European Conference on Computer Vision (ECCV), pages 68-84, 2018.","title":"Boosted attention: Leveraging human attention for image captioning","authors":"Shi Chen, Qi Zhao","year":"2018","venue":"Proceedings of the European Conference on Computer Vision (ECCV)","doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Cornia et al., 2018a] Marcella Cornia, Lorenzo Baraldi, Giuseppe Serra, and Rita Cucchiara. Paying more attention to saliency: Im- age captioning with saliency and context attention. ACM Trans- actions on Multimedia Computing, Communications, and Appli- cations (TOMM), 14(2):1-21, 2018.","title":"Paying more attention to saliency: Image captioning with saliency and context attention","authors":"Cornia","year":"2018","venue":"ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)","doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Cornia et al., 2018b] Marcella Cornia, Lorenzo Baraldi, Giuseppe Serra, and Rita Cucchiara. Predicting human eye fixations via an lstm-based saliency attentive model. IEEE Transactions on Image Processing, 27(10):5142-5154, 2018.","title":"Predicting human eye fixations via an lstm-based saliency attentive model","authors":"Cornia","year":"2018","venue":"IEEE Transactions on Image Processing","doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Das et al., 2017] Abhishek Das, Harsh Agrawal, Larry Zitnick, Devi Parikh, and Dhruv Batra. Human attention in visual ques- tion answering: Do humans and deep networks look at the same regions? Computer Vision and Image Understanding, 163:90- 100, 2017.","title":"Human attention in visual question answering: Do humans and deep networks look at the same regions?","authors":"Abhishek Das, Harsh Agrawal, Larry Zitnick, Devi Parikh, Dhruv Batra","year":"2017","venue":"Computer Vision and Image Understanding","doi":null,"url":null,"internal_url":null},{"position":22,"raw":"[Deng et al., 2019] Tao Deng, Hongmei Yan, Long Qin, Thuyen Ngo, and BS Manjunath. How do drivers allocate their poten- tial attention? driving fixation prediction via convolutional neu- ral networks. IEEE Transactions on Intelligent Transportation Systems, 2019.","title":"How do drivers allocate their potential attention? driving fixation prediction via convolutional neural networks","authors":"Tao Deng, Hongmei Yan, Long Qin, Thuyen Ngo, Manjunath","year":"2019","venue":"IEEE Transactions on Intelligent Transportation Systems","doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Emery, 2000] Nathan J Emery. The eyes have it: the neuroethol- ogy, function and evolution of social gaze. Neuroscience & biobehavioral reviews, 24(6):581-604, 2000.","title":"The eyes have it: the neuroethology, function and evolution of social gaze","authors":"Nathan J Emery, Emery","year":"2000","venue":"Neuroscience & biobehavioral reviews","doi":null,"url":null,"internal_url":null},{"position":24,"raw":"[Fang et al., 2015] Rui Fang, Malcolm Doering, and Joyce Y Chai. Embodied collaborative referring expression generation in situ- ated human-robot interaction. In Proceedings of the Tenth An- nual ACM/IEEE International Conference on Human-Robot In- teraction, pages 271-278, 2015.","title":"Embodied collaborative referring expression generation in situated human-robot interaction","authors":"Rui Fang, Malcolm Doering, Joyce Y Chai","year":"2015","venue":"Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction","doi":null,"url":null,"internal_url":null},{"position":25,"raw":"[Fiore et al., 2013] Stephen M Fiore, Travis J Wiltshire, Emilio JC Lobato, Florian G Jentsch, Wesley H Huang, and Benjamin Ax- elrod. Toward understanding social cues and signals in human- robot interaction: effects of robot gaze and proxemic behavior. Frontiers in psychology, 4:859, 2013.","title":"Toward understanding social cues and signals in humanrobot interaction: effects of robot gaze and proxemic behavior","authors":"Travis J Stephen M Fiore, Wiltshire, J C Emilio, Florian G Lobato, Wesley H Jentsch, Benjamin Huang, Axelrod","year":"2013","venue":"Frontiers in psychology","doi":null,"url":null,"internal_url":null},{"position":26,"raw":"[Hayhoe, 2017] Mary M Hayhoe. Vision and action. Annual review of vision science, 3:389-413, 2017.","title":"Vision and action","authors":"Mary M Hayhoe","year":"2017","venue":"Annual review of vision science","doi":null,"url":null,"internal_url":null},{"position":27,"raw":"[He et al., 2019a] Sen He, Hamed R Tavakoli, Ali Borji, Yang Mi, and Nicolas Pugeault. Understanding and visualizing deep visual saliency models. In Proceedings of the IEEE conference on com- puter vision and pattern recognition, pages 10206-10215, 2019.","title":"Understanding and visualizing deep visual saliency models","authors":"He","year":"2019","venue":"Proceedings of the IEEE conference on computer vision and pattern recognition","doi":null,"url":null,"internal_url":null},{"position":28,"raw":"[He et al., 2019b] Sen He, Hamed R Tavakoli, Ali Borji, and Nico- las Pugeault. Human attention in image captioning: Dataset and analysis. In Proceedings of the IEEE International Conference on Computer Vision, pages 8529-8538, 2019.","title":"Human attention in image captioning: Dataset and analysis","authors":"He","year":"2019","venue":"Proceedings of the IEEE International Conference on Computer Vision","doi":null,"url":null,"internal_url":null},{"position":29,"raw":"[Henderson et al., 2018] John M Henderson, Taylor R Hayes, Gwendolyn Rehrig, and Fernanda Ferreira. Meaning guides at- tention during real-world scene description. Scientific reports, 8(1):1-9, 2018.","title":"Meaning guides attention during real-world scene description","authors":"Taylor R John M Henderson, Gwendolyn Hayes, Fernanda Rehrig, Ferreira","year":"2018","venue":"Scientific reports","doi":null,"url":null,"internal_url":null},{"position":30,"raw":"[Huang and Mutlu, 2016] Chien-Ming Huang and Bilge Mutlu. Anticipatory robot control for efficient human-robot collabo- ration. In 2016 11th ACM/IEEE international conference on human-robot interaction, pages 83-90. IEEE, 2016.","title":"Anticipatory robot control for efficient human-robot collaboration","authors":"Chien-Ming Huang, Bilge Mutlu","year":"2016","venue":"11th ACM/IEEE international conference on human-robot interaction","doi":null,"url":null,"internal_url":null},{"position":31,"raw":"[Huang et al., 2017] Qiong Huang, Ashok Veeraraghavan, and Ashutosh Sabharwal. Tabletgaze: dataset and analysis for un- constrained appearance-based gaze estimation in mobile tablets. Machine Vision and Applications, 28(5-6):445-461, 2017.","title":"Tabletgaze: dataset and analysis for unconstrained appearance-based gaze estimation in mobile tablets","authors":"Qiong Huang, Ashok Veeraraghavan, Ashutosh Sabharwal","year":"2017","venue":"Machine Vision and Applications","doi":null,"url":null,"internal_url":null},{"position":32,"raw":"[Huang et al., 2019] Sandy H Huang, Isabella Huang, Ravi Pandya, and Anca D Dragan. Nonverbal robot feedback for human teach- ers. Conference on Robot Learning, 2019.","title":"Nonverbal robot feedback for human teachers","authors":"H Sandy, Isabella Huang, Ravi Huang, Anca D Pandya, Dragan","year":"2019","venue":"Conference on Robot Learning","doi":null,"url":null,"internal_url":null},{"position":33,"raw":"[Hutt et al., 2016] Stephen Hutt, Caitlin Mills, Shelby White, Patrick J Donnelly, and Sidney K D'Mello. The eyes have it: Gaze-based detection of mind wandering during learning with an intelligent tutoring system. International Educational Data Min- ing Society, 2016.","title":"The eyes have it: Gaze-based detection of mind wandering during learning with an intelligent tutoring system","authors":"Stephen Hutt, Caitlin Mills, Shelby White, Patrick J Donnelly, Sidney K D' Mello","year":"2016","venue":"International Educational Data Mining Society","doi":null,"url":null,"internal_url":null},{"position":34,"raw":"[Itti et al., 1998] Laurent Itti, Christof Koch, and Ernst Niebur. A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis & Machine Intelligence, (11):1254-1259, 1998.","title":"A model of saliency-based visual attention for rapid scene analysis","authors":"Laurent Itti, Christof Koch, Ernst Niebur","year":"1998","venue":"IEEE Transactions on Pattern Analysis & Machine Intelligence","doi":null,"url":null,"internal_url":null},{"position":35,"raw":"[Jaques et al., 2014] Natasha Jaques, Cristina Conati, Jason M Harley, and Roger Azevedo. Predicting affect from gaze data during interaction with an intelligent tutoring system. In Interna- tional Conference on Intelligent Tutoring Systems, pages 29-38. Springer, 2014.","title":"Predicting affect from gaze data during interaction with an intelligent tutoring system","authors":"Natasha Jaques, Cristina Conati, Jason M Harley, Roger Azevedo","year":"2014","venue":"International Conference on Intelligent Tutoring Systems","doi":null,"url":null,"internal_url":null},{"position":36,"raw":"[Jetley et al., 2016] Saumya Jetley, Naila Murray, and Eleonora Vig. End-to-end saliency mapping via probability distribution prediction. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 5753-5761, 2016.","title":"End-to-end saliency mapping via probability distribution prediction","authors":"Saumya Jetley, Naila Murray, Eleonora Vig","year":"2016","venue":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":37,"raw":"[Jiang et al., 2015] Ming Jiang, Shengsheng Huang, Juanyong Duan, and Qi Zhao. Salicon: Saliency in context. In Proceedings of the IEEE conference on computer vision and pattern recogni- tion, pages 1072-1080, 2015.","title":"Salicon: Saliency in context","authors":"Ming Jiang, Shengsheng Huang, Juanyong Duan, Qi Zhao","year":"2015","venue":"Proceedings of the IEEE conference on computer vision and pattern recognition","doi":null,"url":null,"internal_url":null},{"position":38,"raw":"[Karessli et al., 2017] Nour Karessli, Zeynep Akata, Bernt Schiele, and Andreas Bulling. Gaze embeddings for zero-shot image clas- sification. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 4525-4534, 2017.","title":"Gaze embeddings for zero-shot image classification","authors":"Nour Karessli, Zeynep Akata, Bernt Schiele, Andreas Bulling","year":"2017","venue":"Proceedings of the IEEE conference on computer vision and pattern recognition","doi":null,"url":null,"internal_url":null},{"position":39,"raw":"[Krafka et al., 2016] Kyle Krafka, Aditya Khosla, Petr Kellnhofer, Harini Kannan, Suchendra Bhandarkar, Wojciech Matusik, and Antonio Torralba. Eye tracking for everyone. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 2176-2184, 2016.","title":"Eye tracking for everyone","authors":"Kyle Krafka, Aditya Khosla, Petr Kellnhofer, Harini Kannan, Suchendra Bhandarkar, Wojciech Matusik, Antonio Torralba","year":"2016","venue":"Proceedings of the IEEE conference on computer vision and pattern recognition","doi":null,"url":null,"internal_url":null},{"position":40,"raw":"[Kruthiventi et al., 2017] Srinivas SS Kruthiventi, Kumar Ayush, and Radhakrishnan Venkatesh Babu. Deepfix: A fully convo- lutional neural network for predicting human eye fixations. IEEE Transactions on Image Processing, 2017.","title":"Deepfix: A fully convolutional neural network for predicting human eye fixations","authors":"S S Srinivas, Kumar Kruthiventi, Radhakrishnan Ayush, Babu Venkatesh","year":"2017","venue":"IEEE Transactions on Image Processing","doi":null,"url":null,"internal_url":null},{"position":41,"raw":"[Kümmerer et al., 2016] Matthias Kümmerer, Thomas SA Wallis, and Matthias Bethge. Deepgaze ii: Reading fixations from deep features trained on object recognition. arXiv preprint arXiv:1610.01563, 2016.","title":"Deepgaze ii: Reading fixations from deep features trained on object recognition","authors":"Matthias Kümmerer, Thomas Sa Wallis, Matthias Bethge","year":"2016","venue":null,"doi":null,"url":null,"internal_url":null},{"position":42,"raw":"[Li et al., 2014] Yin Li, Xiaodi Hou, Christof Koch, James M Rehg, and Alan L Yuille. The secrets of salient object segmentation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 280-287, 2014.","title":"The secrets of salient object segmentation","authors":"Yin Li, Xiaodi Hou, Christof Koch, James M Rehg, Alan L Yuille","year":"2014","venue":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":43,"raw":"[Li et al., 2018] Yin Li, Miao Liu, and James M Rehg. In the eye of beholder: Joint learning of gaze and actions in first person video. In Proceedings of the European Conference on Computer Vision (ECCV), pages 619-635, 2018.","title":"In the eye of beholder: Joint learning of gaze and actions in first person video","authors":"Yin Li, Miao Liu, James M Rehg","year":"2018","venue":"Proceedings of the European Conference on Computer Vision (ECCV)","doi":null,"url":null,"internal_url":null},{"position":44,"raw":"[Liu et al., 2019] Congcong Liu, Yuying Chen, Lei Tai, Haoyang Ye, Ming Liu, and Bertram E Shi. A gaze model improves au- tonomous driving. In Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications, page 33. ACM, 2019.","title":"A gaze model improves autonomous driving","authors":"Congcong Liu, Yuying Chen, Lei Tai, Haoyang Ye, Ming Liu, Bertram E Shi","year":"2019","venue":"Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications","doi":null,"url":null,"internal_url":null},{"position":45,"raw":"[Mathe and Sminchisescu, 2014] Stefan Mathe and Cristian Smin- chisescu. Actions in the eye: Dynamic gaze datasets and learnt saliency models for visual recognition. IEEE transactions on pat- tern analysis and machine intelligence, 37(7):1408-1424, 2014.","title":"Actions in the eye: Dynamic gaze datasets and learnt saliency models for visual recognition","authors":"Sminchisescu Mathe","year":"2014","venue":"IEEE transactions on pattern analysis and machine intelligence","doi":null,"url":null,"internal_url":null},{"position":46,"raw":"[Mnih et al., 2014] Volodymyr Mnih, Nicolas Heess, Alex Graves, et al. Recurrent models of visual attention. In Advances in neural information processing systems, pages 2204-2212, 2014.","title":"Recurrent models of visual attention","authors":"Volodymyr Mnih, Nicolas Heess, Alex Graves","year":"2014","venue":"Advances in neural information processing systems","doi":null,"url":null,"internal_url":null},{"position":47,"raw":"[Moon et al., 2014] AJung Moon, Daniel M Troniak, Brian Glee- son, Matthew KXJ Pan, Minhua Zheng, Benjamin A Blumer, Karon MacLean, and Elizabeth A Croft. Meet me where i'm gazing: how shared attention gaze affects human-robot handover timing. In Proceedings of the 2014 ACM/IEEE international con- ference on Human-robot interaction, pages 334-341, 2014.","title":"Meet me where i'm gazing: how shared attention gaze affects human-robot handover timing","authors":"Moon","year":"2014","venue":"Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction","doi":null,"url":null,"internal_url":null},{"position":48,"raw":"[Nguyen et al., 2018] Tam V Nguyen, Qi Zhao, and Shuicheng Yan. Attentive systems: A survey. International Journal of Com- puter Vision, 126(1):86-110, 2018.","title":"Attentive systems: A survey","authors":"Qi Tam V Nguyen, Shuicheng Zhao, Yan","year":"2018","venue":"International Journal of Computer Vision","doi":null,"url":null,"internal_url":null},{"position":49,"raw":"[Palazzi et al., 2018] Andrea Palazzi, Davide Abati, Simone Calderara, Francesco Solera, and Rita Cucchiara. Predicting the driver's focus of attention: the dr (eye) ve project. IEEE transac- tions on pattern analysis and machine intelligence, 2018.","title":"Predicting the driver's focus of attention: the dr (eye) ve project","authors":"Andrea Palazzi, Davide Abati, Simone Calderara, Francesco Solera, Rita Cucchiara","year":"2018","venue":null,"doi":null,"url":null,"internal_url":null},{"position":50,"raw":"[Palinko et al., 2016] Oskar Palinko, Francesco Rea, Giulio San- dini, and Alessandra Sciutti. Robot reading human gaze: Why eye tracking is better than head tracking for human-robot collabo- ration. In 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 5048-5054. IEEE, 2016.","title":"Robot reading human gaze: Why eye tracking is better than head tracking for human-robot collaboration","authors":"Oskar Palinko, Francesco Rea, Giulio Sandini, Alessandra Sciutti","year":"2016","venue":"IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","doi":null,"url":null,"internal_url":null},{"position":51,"raw":"[Papadopoulos et al., 2014] Dim P Papadopoulos, Alasdair DF Clarke, Frank Keller, and Vittorio Ferrari. Training object class detectors from eye tracking data. In European conference on computer vision, pages 361-376. Springer, 2014.","title":"Training object class detectors from eye tracking data","authors":"Papadopoulos","year":"2014","venue":"European conference on computer vision","doi":null,"url":null,"internal_url":null},{"position":52,"raw":"[Papoutsaki et al., 2016] Alexandra Papoutsaki, Patsorn Sangkloy, James Laskey, Nediyana Daskalova, Jeff Huang, and James Hays. Webgazer: Scalable webcam eye tracking using user in- teractions. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence-IJCAI 2016, 2016.","title":"Webgazer: Scalable webcam eye tracking using user interactions","authors":"Papoutsaki","year":"2016","venue":"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence-IJCAI 2016","doi":null,"url":null,"internal_url":"/proceedings/2016/540"},{"position":53,"raw":"[Park et al., 2018] Seonwook Park, Adrian Spurr, and Otmar Hilliges. Deep pictorial gaze estimation. In Proceedings of the European Conference on Computer Vision (ECCV), pages 721- 738, 2018.","title":"Seonwook Park, Adrian Spurr, and Otmar Hilliges. Deep pictorial gaze estimation","authors":"Park","year":"2018","venue":"Proceedings of the European Conference on Computer Vision (ECCV)","doi":null,"url":null,"internal_url":null},{"position":54,"raw":"[Penkov et al., 2017] Svetlin Penkov, Alejandro Bordallo, and Sub- ramanian Ramamoorthy. Physical symbol grounding and in- stance learning through demonstration and eye tracking. In 2017 IEEE International Conference on Robotics and Automa- tion (ICRA), pages 5921-5928. IEEE, 2017.","title":"Physical symbol grounding and instance learning through demonstration and eye tracking","authors":"Svetlin Penkov, Alejandro Bordallo, Subramanian Ramamoorthy","year":"2017","venue":"2017 IEEE International Conference on Robotics and Automation (ICRA)","doi":null,"url":null,"internal_url":null},{"position":55,"raw":"[Posner and Petersen, 1990] Michael I Posner and Steven E Pe- tersen. The attention system of the human brain. Annual review of neuroscience, 13(1):25-42, 1990.","title":"The attention system of the human brain","authors":"I Michael, Steven E Posner, Petersen","year":"1990","venue":"Annual review of neuroscience","doi":null,"url":null,"internal_url":null},{"position":56,"raw":"[Qiao et al., 2018] Tingting Qiao, Jianfeng Dong, and Duanqing Xu. Exploring human-like attention supervision in visual ques- tion answering. In Thirty-Second AAAI Conference on Artificial Intelligence, 2018.","title":"Exploring human-like attention supervision in visual question answering","authors":"Tingting Qiao, Jianfeng Dong, Duanqing Xu","year":"2018","venue":"Thirty-Second AAAI Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":57,"raw":"[Ravichandar et al., 2018] Harish Chaandar Ravichandar, Avnish Kumar, and Ashwin Dani. Gaze and motion information fusion for human intention inference. International Journal of Intelli- gent Robotics and Applications, 2(2):136-148, 2018.","title":"Gaze and motion information fusion for human intention inference","authors":"Avnish Harish Chaandar Ravichandar, Ashwin Kumar, Dani","year":"2018","venue":"International Journal of Intelligent Robotics and Applications","doi":null,"url":null,"internal_url":null},{"position":58,"raw":"[Recasens et al., 2015] Adria Recasens, Aditya Khosla, Carl Von- drick, and Antonio Torralba. Where are they looking? In Ad- vances in Neural Information Processing Systems, pages 199- 207, 2015.","title":"Where are they looking?","authors":"Adria Recasens, Aditya Khosla, Carl Vondrick, Antonio Torralba","year":"2015","venue":"Advances in Neural Information Processing Systems","doi":null,"url":null,"internal_url":null},{"position":59,"raw":"[Recasens et al., 2017] Adria Recasens, Carl Vondrick, Aditya Khosla, and Antonio Torralba. Following gaze in video. In Pro- ceedings of the IEEE International Conference on Computer Vi- sion, pages 1435-1443, 2017.","title":"Following gaze in video","authors":"Adria Recasens, Carl Vondrick, Aditya Khosla, Antonio Torralba","year":"2017","venue":"Proceedings of the IEEE International Conference on Computer Vision","doi":null,"url":null,"internal_url":null},{"position":60,"raw":"[Rich et al., 2010] Charles Rich, Brett Ponsler, Aaron Holroyd, and Candace L Sidner. Recognizing engagement in human-robot in- teraction. In 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pages 375-382. IEEE, 2010.","title":"Recognizing engagement in human-robot interaction","authors":"Charles Rich, Brett Ponsler, Aaron Holroyd, Candace L Sidner","year":"2010","venue":"5th ACM/IEEE International Conference on Human-Robot Interaction (HRI)","doi":null,"url":null,"internal_url":null},{"position":61,"raw":"[Richter et al., 2016] Viktor Richter, Birte Carlmeyer, Florian Lier, Sebastian Meyer zu Borgsen, David Schlangen, Franz Kummert, Sven Wachsmuth, and Britta Wrede. Are you talking to me? im- proving the robustness of dialogue systems in a multi party hri scenario by incorporating gaze direction and lip movement of at- tendees. In Proceedings of the Fourth International Conference on Human Agent Interaction, pages 43-50, 2016.","title":"Are you talking to me? improving the robustness of dialogue systems in a multi party hri scenario by incorporating gaze direction and lip movement of attendees","authors":"Viktor Richter, Birte Carlmeyer, Florian Lier, Sebastian Meyer Zu Borgsen, David Schlangen, Franz Kummert, Sven Wachsmuth, Britta Wrede","year":"2016","venue":"Proceedings of the Fourth International Conference on Human Agent Interaction","doi":null,"url":null,"internal_url":null},{"position":62,"raw":"[Ruhland et al., 2015] Kerstin Ruhland, Christopher E Peters, Sean Andrist, Jeremy B Badler, Norman I Badler, Michael Gleicher, Bilge Mutlu, and Rachel McDonnell. A review of eye gaze in vir- tual agents, social robotics and hci: Behaviour generation, user interaction and perception. In Computer graphics forum, vol- ume 34, pages 299-326. Wiley Online Library, 2015.","title":"A review of eye gaze in virtual agents, social robotics and hci: Behaviour generation, user interaction and perception","authors":"Kerstin Ruhland, Christopher E Peters, Sean Andrist, Jeremy B Badler, Norman I Badler, Michael Gleicher, Bilge Mutlu, Rachel Mcdonnell","year":"2015","venue":"Computer graphics forum","doi":null,"url":null,"internal_url":null},{"position":63,"raw":"[Saran et al., 2018] Akanksha Saran, Srinjoy Majumdar, Elaine Schaertl Short, Andrea Thomaz, and Scott Niekum. Human gaze following for human-robot interaction. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 8615-8621. IEEE, 2018.","title":"Human gaze following for human-robot interaction","authors":"Akanksha Saran, Srinjoy Majumdar, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum","year":"2018","venue":"IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","doi":null,"url":null,"internal_url":null},{"position":64,"raw":"[Saran et al., 2019] Akanksha Saran, Elaine Schaertl Short, Andrea Thomaz, and Scott Niekum. Understanding teacher gaze patterns for robot learning. Conference on Robot Learning, 2019.","title":"Understanding teacher gaze patterns for robot learning","authors":"Akanksha Saran, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum","year":"2019","venue":"Conference on Robot Learning","doi":null,"url":null,"internal_url":null},{"position":65,"raw":"[Shafti et al., 2019] Ali Shafti, Pavel Orlov, and A Aldo Faisal. Gaze-based, context-aware robotic system for assisted reaching and grasping. In 2019 International Conference on Robotics and Automation (ICRA), pages 863-869. IEEE, 2019.","title":"Gaze-based, context-aware robotic system for assisted reaching and grasping","authors":"Ali Shafti, Pavel Orlov, Aldo Faisal","year":"2019","venue":"2019 International Conference on Robotics and Automation (ICRA)","doi":null,"url":null,"internal_url":null},{"position":66,"raw":"[Shen et al., 2018] Yang Shen, Bingbing Ni, Zefan Li, and Ning Zhuang. Egocentric activity prediction via event modulated at- tention. In Proceedings of the European Conference on Computer Vision (ECCV), pages 197-212, 2018.","title":"Egocentric activity prediction via event modulated attention","authors":"Yang Shen, Bingbing Ni, Zefan Li, Ning Zhuang","year":"2018","venue":"Proceedings of the European Conference on Computer Vision (ECCV)","doi":null,"url":null,"internal_url":null},{"position":67,"raw":"[Shrivastava et al., 2017] Ashish Shrivastava, Tomas Pfister, Oncel Tuzel, Joshua Susskind, Wenda Wang, and Russell Webb. Learn- ing from simulated and unsupervised images through adversarial training. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 2107-2116, 2017.","title":"Learning from simulated and unsupervised images through adversarial training","authors":"Ashish Shrivastava, Tomas Pfister, Oncel Tuzel, Joshua Susskind, Wenda Wang, Russell Webb","year":"2017","venue":"Proceedings of the IEEE conference on computer vision and pattern recognition","doi":null,"url":null,"internal_url":null},{"position":68,"raw":"[Sudhakaran et al., 2019] Swathikiran Sudhakaran, Sergio Es- calera, and Oswald Lanz. Lsta: Long short-term attention for egocentric action recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 9954-9963, 2019.","title":"Lsta: Long short-term attention for egocentric action recognition","authors":"Sudhakaran","year":"2019","venue":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":69,"raw":"[Sugano and Bulling, 2016] Yusuke Sugano and Andreas Bulling. Seeing with humans: Gaze-assisted neural image captioning. arXiv preprint arXiv:1608.05203, 2016.","title":"Seeing with humans: Gaze-assisted neural image captioning","authors":"Bulling Sugano, Yusuke Sugano, Andreas Bulling","year":"2016","venue":null,"doi":null,"url":null,"internal_url":null},{"position":70,"raw":"[Tavakoli et al., 2017] Hamed R Tavakoli, Rakshith Shetty, Ali Borji, and Jorma Laaksonen. Paying attention to descriptions generated by image captioning models. In Proceedings of the IEEE International Conference on Computer Vision, pages 2487- 2496, 2017.","title":"Paying attention to descriptions generated by image captioning models","authors":"Rakshith Hamed R Tavakoli, Ali Shetty, Jorma Borji, Laaksonen","year":"2017","venue":"Proceedings of the IEEE International Conference on Computer Vision","doi":null,"url":null,"internal_url":null},{"position":71,"raw":"[Tavakoli et al., 2019] Hamed Rezazadegan Tavakoli, Esa Rahtu, Juho Kannala, and Ali Borji. Digging deeper into egocentric gaze prediction. In 2019 IEEE Winter Conference on Applications of Computer Vision, pages 273-282. IEEE, 2019.","title":"Digging deeper into egocentric gaze prediction","authors":"Esa Hamed Rezazadegan Tavakoli, Juho Rahtu, Ali Kannala, Borji","year":"2019","venue":"IEEE Winter Conference on Applications of Computer Vision","doi":null,"url":null,"internal_url":null},{"position":72,"raw":"[Thomaz et al., 2016] Andrea Thomaz, Guy Hoffman, Maya Cak- mak, et al. Computational human-robot interaction. Foundations and Trends R in Robotics, 4(2-3):105-223, 2016.","title":"Computational human-robot interaction","authors":"Andrea Thomaz, Guy Hoffman, Maya Cakmak","year":"2016","venue":"Foundations and Trends R in Robotics","doi":null,"url":null,"internal_url":null},{"position":73,"raw":"[Vaidyanathan et al., 2018] Preethi Vaidyanathan, Emily Prud'hommeaux, Jeff B Pelz, and Cecilia Ovesdotter Alm. Snag: Spoken narratives and gaze dataset. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pages 132-137, 2018.","title":"Snag: Spoken narratives and gaze dataset","authors":"Preethi Vaidyanathan, Emily Prud'hommeaux, Jeff B Pelz, Cecilia Ovesdotter, Alm","year":"2018","venue":"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics","doi":null,"url":null,"internal_url":null},{"position":74,"raw":"[van Miltenburg et al., 2018] Emiel van Miltenburg, Akos Kádár, Ruud Koolen, and Emiel Krahmer. Didec: The dutch image de- scription and eye-tracking corpus. In Proceedings of the 27th International Conference on Computational Linguistics, pages 3658-3669, 2018.","title":"Didec: The dutch image description and eye-tracking corpus","authors":"Akos Emiel Van Miltenburg, Ruud Kádár, Emiel Koolen, Krahmer","year":"2018","venue":"Proceedings of the 27th International Conference on Computational Linguistics","doi":null,"url":null,"internal_url":null},{"position":75,"raw":"[Vaswani et al., 2017] Ashish Vaswani, Noam Shazeer, Niki Par- mar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. Attention is all you need. In Ad- vances in neural information processing systems, pages 5998- 6008, 2017.","title":"Attention is all you need","authors":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, Illia Polosukhin","year":"2017","venue":"Advances in neural information processing systems","doi":null,"url":null,"internal_url":null},{"position":76,"raw":"[Wang et al., 2018] Wenguan Wang, Jianbing Shen, Fang Guo, Ming-Ming Cheng, and Ali Borji. Revisiting video saliency: A large-scale benchmark and a new model. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 4894-4903, 2018.","title":"Revisiting video saliency: A large-scale benchmark and a new model","authors":"Wang","year":"2018","venue":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":77,"raw":"[Wood et al., 2015] Erroll Wood, Tadas Baltrusaitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling. Rendering of eyes for eye-shape registration and gaze estima- tion. In Proceedings of the IEEE International Conference on Computer Vision, pages 3756-3764, 2015.","title":"Rendering of eyes for eye-shape registration and gaze estimation","authors":"Erroll Wood, Tadas Baltrusaitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, Andreas Bulling","year":"2015","venue":"Proceedings of the IEEE International Conference on Computer Vision","doi":null,"url":null,"internal_url":null},{"position":78,"raw":"[Xia et al., 2018] Ye Xia, Danqing Zhang, Jinkyu Kim, Ken Nakayama, Karl Zipser, and David Whitney. Predicting driver attention in critical situations. In Asian conference on computer vision, pages 658-674. Springer, 2018.","title":"Predicting driver attention in critical situations","authors":"Ye Xia, Danqing Zhang, Jinkyu Kim, Ken Nakayama, Karl Zipser, David Whitney","year":"2018","venue":"Asian conference on computer vision","doi":null,"url":null,"internal_url":null},{"position":79,"raw":"[Xu et al., 2014] Juan Xu, Ming Jiang, Shuo Wang, Mohan S Kankanhalli, and Qi Zhao. Predicting human gaze beyond pixels. Journal of vision, 14(1):28-28, 2014.","title":"Predicting human gaze beyond pixels","authors":"Xu","year":"2014","venue":"Journal of vision","doi":null,"url":null,"internal_url":null},{"position":80,"raw":"[Xu et al., 2018] Yanyu Xu, Yanbing Dong, Junru Wu, Zhengzhong Sun, Zhiru Shi, Jingyi Yu, and Shenghua Gao. Gaze prediction in dynamic 360 immersive videos. In proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 5333-5342, 2018.","title":"Gaze prediction in dynamic 360 immersive videos","authors":"Yanyu Xu, Yanbing Dong, Junru Wu, Zhengzhong Sun, Zhiru Shi, Jingyi Yu, Shenghua Gao","year":"2018","venue":"proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":81,"raw":"[Yu and Smith, 2011] Chen Yu and Linda B Smith. What you learn is what you see: using eye movements to study infant cross- situational word learning. Developmental science, 14(2):165- 180, 2011.","title":"What you learn is what you see: using eye movements to study infant crosssituational word learning","authors":"Chen Yu, Linda B Smith","year":"2011","venue":"Developmental science","doi":null,"url":null,"internal_url":null},{"position":82,"raw":"[Yu et al., 2014] Mingxin Yu, Yingzi Lin, David Schmidt, Xi- angzhou Wang, and Yu Wang. Human-robot interaction based on gaze gestures for the drone teleoperation. Journal of Eye Move- ment Research, 7(4):1-14, 2014.","title":"Human-robot interaction based on gaze gestures for the drone teleoperation","authors":"Mingxin Yu, Yingzi Lin, David Schmidt, Xiangzhou Wang, Yu Wang","year":"2014","venue":"Journal of Eye Movement Research","doi":null,"url":null,"internal_url":null},{"position":83,"raw":"[Yu et al., 2017] Youngjae Yu, Jongwook Choi, Yeonhwa Kim, Kyung Yoo, Sang-Hun Lee, and Gunhee Kim. Supervising neu- ral attention models for video captioning by human gaze data. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 490-498, 2017.","title":"Supervising neural attention models for video captioning by human gaze data","authors":"Youngjae Yu, Jongwook Choi, Yeonhwa Kim, Kyung Yoo, Sang-Hun Lee, Gunhee Kim","year":"2017","venue":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":84,"raw":"[Yun et al., 2013] Kiwon Yun, Yifan Peng, Dimitris Samaras, Gre- gory J Zelinsky, and Tamara L Berg. Studying relationships be- tween human gaze, description, and computer vision. In Pro- ceedings of the IEEE Conference on Computer Vision and Pat- tern Recognition, pages 739-746, 2013.","title":"Studying relationships between human gaze, description, and computer vision","authors":"Kiwon Yun, Yifan Peng, Dimitris Samaras, Gregory J Zelinsky, Tamara L Berg","year":"2013","venue":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":85,"raw":"[Zhang et al., 2015] Xucong Zhang, Yusuke Sugano, Mario Fritz, and Andreas Bulling. Appearance-based gaze estimation in the wild. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 4511-4520, 2015.","title":"Appearance-based gaze estimation in the wild","authors":"Zhang","year":"2015","venue":"Proceedings of the IEEE conference on computer vision and pattern recognition","doi":null,"url":null,"internal_url":null},{"position":86,"raw":"[Zhang et al., 2017] Xucong Zhang, Yusuke Sugano, Mario Fritz, and Andreas Bulling. Mpiigaze: Real-world dataset and deep appearance-based gaze estimation. IEEE transactions on pattern analysis and machine intelligence, 41(1):162-175, 2017.","title":"Mpiigaze: Real-world dataset and deep appearance-based gaze estimation","authors":"Zhang","year":"2017","venue":"IEEE transactions on pattern analysis and machine intelligence","doi":null,"url":null,"internal_url":null},{"position":87,"raw":"[Zhang et al., 2018a] Ruohan Zhang, Zhuode Liu, Luxin Zhang, Jake A Whritner, Karl S Muller, Mary M Hayhoe, and Dana H Ballard. Agil: Learning attention from human for visuomotor tasks. In Proceedings of the European Conference on Computer Vision (ECCV), pages 663-679, 2018.","title":"Agil: Learning attention from human for visuomotor tasks","authors":"Zhang","year":"2018","venue":"Proceedings of the European Conference on Computer Vision (ECCV)","doi":null,"url":null,"internal_url":null},{"position":88,"raw":"[Zhang et al., 2018b] Ziheng Zhang, Yanyu Xu, Jingyi Yu, and Shenghua Gao. Saliency detection in 360 videos. In Proceed- ings of the European Conference on Computer Vision (ECCV), pages 488-503, 2018.","title":"Saliency detection in 360 videos","authors":"Zhang","year":"2018","venue":"Proceedings of the European Conference on Computer Vision (ECCV)","doi":null,"url":null,"internal_url":null},{"position":89,"raw":"[Zhang et al., 2019a] Ruohan Zhang, Faraz Torabi, Lin Guan, Dana H Ballard, and Peter Stone. Leveraging human guidance for deep reinforcement learning tasks. In Proceedings of the 28th International Joint Conference on Artificial Intelligence, pages 6339-6346. AAAI Press, 2019.","title":"Leveraging human guidance for deep reinforcement learning tasks","authors":"Zhang","year":"2019","venue":"Proceedings of the 28th International Joint Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":"/proceedings/2019/884"},{"position":90,"raw":"[Zhang et al., 2019b] Ruohan Zhang, Calen Walshe, Zhuode Liu, Lin Guan, Karl S Muller, Jake A Whritner, Luxin Zhang, Mary M Hayhoe, and Dana H Ballard. Atari-head: Atari hu- man eye-tracking and demonstration dataset. arXiv preprint arXiv:1903.06754, 2019.","title":"Atari-head: Atari human eye-tracking and demonstration dataset","authors":"Zhang","year":"2019","venue":null,"doi":null,"url":null,"internal_url":null},{"position":91,"raw":"[Zuo et al., 2018] Zheming Zuo, Longzhi Yang, Yonghong Peng, Fei Chao, and Yanpeng Qu. Gaze-informed egocentric action recognition for memory aid systems. IEEE Access, 6:12894- 12904, 2018.","title":"Gaze-informed egocentric action recognition for memory aid systems","authors":"Zuo","year":"2018","venue":"IEEE Access","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}