no code implementations • 21 Oct 2022 • Mengdi Xu, Peide Huang, Yaru Niu, Visak Kumar, JieLin Qiu, Chao Fang, Kuan-Hui Lee, Xuewei Qi, Henry Lam, Bo Li, Ding Zhao
One key challenge for multi-task Reinforcement learning (RL) in practice is the absence of task indicators.
no code implementations • 28 Mar 2022 • Vitor Guizilini, Kuan-Hui Lee, Rares Ambrus, Adrien Gaidon
However, the simultaneous self-supervised learning of depth and scene flow is ill-posed, as there are infinitely many combinations that result in the same 3D point.
1 code implementation • 30 Apr 2021 • Nishant Rai, Ehsan Adeli, Kuan-Hui Lee, Adrien Gaidon, Juan Carlos Niebles
Labeling videos at scale is impractical.
1 code implementation • 26 Apr 2021 • Boris Ivanovic, Kuan-Hui Lee, Pavel Tokmakov, Blake Wulfe, Rowan Mcallister, Adrien Gaidon, Marco Pavone
Reasoning about the future behavior of other agents is critical to safe robot navigation.
no code implementations • 24 Nov 2020 • Daisuke Nishiyama, Mario Ynocente Castro, Shirou Maruyama, Shinya Shiroshita, Karim Hamzaoui, Yi Ouyang, Guy Rosman, Jonathan DeCastro, Kuan-Hui Lee, Adrien Gaidon
Automated Vehicles require exhaustive testing in simulation to detect as many safety-critical failures as possible before deployment on public roads.
no code implementations • 11 Nov 2020 • Shinya Shiroshita, Shirou Maruyama, Daisuke Nishiyama, Mario Ynocente Castro, Karim Hamzaoui, Guy Rosman, Jonathan DeCastro, Kuan-Hui Lee, Adrien Gaidon
Traffic simulators are important tools in autonomous driving development.
no code implementations • 3 Aug 2020 • Kuan-Hui Lee, Matthew Kliemann, Adrien Gaidon, Jie Li, Chao Fang, Sudeep Pillai, Wolfram Burgard
In autonomous driving, accurately estimating the state of surrounding obstacles is critical for safe and robust path planning.
3 code implementations • ECCV 2020 • Karttikeya Mangalam, Harshayu Girase, Shreyas Agarwal, Kuan-Hui Lee, Ehsan Adeli, Jitendra Malik, Adrien Gaidon
In this work, we present Predicted Endpoint Conditioned Network (PECNet) for flexible human trajectory prediction.
Ranked #1 on Multi Future Trajectory Prediction on ETH/UCY
no code implementations • CVPR 2020 • Boxiao Pan, Haoye Cai, De-An Huang, Kuan-Hui Lee, Adrien Gaidon, Ehsan Adeli, Juan Carlos Niebles
In this paper, we propose a novel spatio-temporal graph model for video captioning that exploits object interactions in space and time.
1 code implementation • 20 Feb 2020 • Bingbin Liu, Ehsan Adeli, Zhangjie Cao, Kuan-Hui Lee, Abhijeet Shenoi, Adrien Gaidon, Juan Carlos Niebles
In addition, we introduce a new dataset designed specifically for autonomous-driving scenarios in areas with dense pedestrian populations: the Stanford-TRI Intent Prediction (STIP) dataset.
no code implementations • 4 Nov 2019 • Karttikeya Mangalam, Ehsan Adeli, Kuan-Hui Lee, Adrien Gaidon, Juan Carlos Niebles
In contrast to the previous work that aims to solve either the task of pose prediction or trajectory forecasting in isolation, we propose a framework to unify the two problems and address the practically useful task of pedestrian locomotion prediction in the wild.
no code implementations • 9 Jun 2019 • Kuan-Hui Lee, Takaaki Tagawa, Jia-En M. Pan, Adrien Gaidon, Bertrand Douillard
Vehicle taillight recognition is an important application for automated driving, especially for intent prediction of ado vehicles and trajectory planning of the ego vehicle.
no code implementations • ICLR 2019 • Kuan-Hui Lee, German Ros, Jie Li, Adrien Gaidon
Deep Learning for Computer Vision depends mainly on the source of supervision. Photo-realistic simulators can generate large-scale automatically labeled syntheticdata, but introduce a domain gap negatively impacting performance.