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Amir Rasouli
Amir Rasouli
Noah's Ark Laboratory
Verified email at huawei.com - Homepage
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Cited by
Cited by
Year
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
7072019
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
3172017
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
2942019
Agreeing to cross: How drivers and pedestrians communicate
A Rasouli, I Kotseruba, JK Tsotsos
2017 IEEE Intelligent Vehicles Symposium (IV), 264-269, 2017
2642017
Understanding pedestrian behavior in complex traffic scenes
A Rasouli, I Kotseruba, JK Tsotsos
IEEE Transactions on Intelligent Vehicles 3 (1), 61-70, 2017
2292017
Joint attention in autonomous driving (JAAD)
I Kotseruba, A Rasouli, JK Tsotsos
arXiv preprint arXiv:1609.04741, 2016
1182016
Pedestrian Action Anticipation using Contextual Feature Fusion in Stacked RNNs
A Rasouli, I Kotseruba, JK Tsotsos
British Machine Vision Conference (BMVC), 2019
1102019
Benchmark for Evaluating Pedestrian Action Prediction
I Kotseruba, A Rasouli, JK Tsotsos
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021
792021
Deep learning for vision-based prediction: A survey
A Rasouli
arXiv preprint arXiv:2007.00095, 2020
502020
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
492021
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
442020
The effect of color space selection on detectability and discriminability of colored objects
A Rasouli, JK Tsotsos
arXiv preprint arXiv:1702.05421, 2017
432017
Joint attention in driver-pedestrian interaction: from theory to practice
A Rasouli, JK Tsotsos
arXiv preprint arXiv:1802.02522, 2018
422018
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
372018
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
342022
Attention-based active visual search for mobile robots
A Rasouli, P Lanillos, G Cheng, JK Tsotsos
Autonomous Robots 44 (2), 131-146, 2020
302020
Towards social autonomous vehicles: Understanding pedestrian-driver interactions
A Rasouli, I Kotseruba, JK Tsotsos
2018 21st International Conference on Intelligent Transportation Systems …, 2018
282018
Visual saliency improves autonomous visual search
A Rasouli, JK Tsotsos
2014 Canadian Conference on Computer and Robot Vision, 111-118, 2014
242014
Do Saliency Models Detect Odd-One-Out Targets? New Datasets and Evaluations
I Kotseruba, C Wloka, A Rasouli, JK Tsotsos
British Machine Vision Conference (BMVC), 2019
212019
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
172021
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