| Autonomous vehicles that interact with pedestrians: A survey of theory and practice A Rasouli, JK Tsotsos IEEE transactions on intelligent transportation systems 21 (3), 900-918, 2019 | 885 | 2019 |
| Are they going to cross? a benchmark dataset and baseline for pedestrian crosswalk behavior A Rasouli, I Kotseruba, JK Tsotsos Proceedings of the IEEE international conference on computer vision …, 2017 | 427 | 2017 |
| Pie: A large-scale dataset and models for pedestrian intention estimation and trajectory prediction A Rasouli, I Kotseruba, T Kunic, JK Tsotsos Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 418 | 2019 |
| Agreeing to cross: How drivers and pedestrians communicate A Rasouli, I Kotseruba, JK Tsotsos 2017 IEEE Intelligent Vehicles Symposium (IV), 264-269, 2017 | 310 | 2017 |
| Understanding pedestrian behavior in complex traffic scenes A Rasouli, I Kotseruba, JK Tsotsos IEEE Transactions on Intelligent Vehicles 3 (1), 61-70, 2017 | 273 | 2017 |
| Pedestrian Action Anticipation using Contextual Feature Fusion in Stacked RNNs A Rasouli, I Kotseruba, JK Tsotsos British Machine Vision Conference (BMVC), 2019 | 150 | 2019 |
| Joint attention in autonomous driving (JAAD) I Kotseruba, A Rasouli, JK Tsotsos arXiv preprint arXiv:1609.04741, 2016 | 137 | 2016 |
| Benchmark for Evaluating Pedestrian Action Prediction I Kotseruba, A Rasouli, JK Tsotsos Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021 | 130 | 2021 |
| Bifold and semantic reasoning for pedestrian behavior prediction A Rasouli, M Rohani, J Luo Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 78 | 2021 |
| Do they want to cross? understanding pedestrian intention for behavior prediction I Kotseruba, A Rasouli, JK Tsotsos 2020 IEEE Intelligent Vehicles Symposium (IV), 1688-1693, 2020 | 70 | 2020 |
| Deep learning for vision-based prediction: A survey A Rasouli arXiv preprint arXiv:2007.00095, 2020 | 57 | 2020 |
| Multi-modal hybrid architecture for pedestrian action prediction A Rasouli, T Yau, M Rohani, J Luo 2022 IEEE intelligent Vehicles symposium (IV), 91-97, 2022 | 53 | 2022 |
| Joint attention in driver-pedestrian interaction: from theory to practice A Rasouli, JK Tsotsos arXiv preprint arXiv:1802.02522, 2018 | 49 | 2018 |
| The effect of color space selection on detectability and discriminability of colored objects A Rasouli, JK Tsotsos arXiv preprint arXiv:1702.05421, 2017 | 48 | 2017 |
| It's not all about size: On the role of data properties in pedestrian detection A Rasouli, I Kotseruba, JK Tsotsos Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018 | 41 | 2018 |
| Towards social autonomous vehicles: Understanding pedestrian-driver interactions A Rasouli, I Kotseruba, JK Tsotsos 2018 21st International Conference on Intelligent Transportation Systems …, 2018 | 40 | 2018 |
| PedFormer: Pedestrian behavior prediction via cross-modal attention modulation and gated multitask learning A Rasouli, I Kotseruba 2023 IEEE International Conference on Robotics and Automation (ICRA), 9844-9851, 2023 | 34 | 2023 |
| Attention-based active visual search for mobile robots A Rasouli, P Lanillos, G Cheng, JK Tsotsos Autonomous Robots 44 (2), 131-146, 2020 | 34 | 2020 |
| Graph-sim: A graph-based spatiotemporal interaction modelling for pedestrian action prediction T Yau, S Malekmohammadi, A Rasouli, P Lakner, M Rohani, J Luo 2021 IEEE International Conference on Robotics and Automation (ICRA), 8580-8586, 2021 | 27 | 2021 |
| LatentFormer: Multi-agent transformer-based interaction modeling and trajectory prediction E Amirloo, A Rasouli, P Lakner, M Rohani, J Luo arXiv preprint arXiv:2203.01880, 2022 | 26 | 2022 |
John K. TsotsosYork University, CanadaEmail được xác minh tại yorku.ca