Pang-Yuan Pao, Shu-Wei Lu, Ze-Yan Lu, Yi-Ting Chen, "Potential Field as Scene Affordance for Behavior Change-Based Visual Risk Object Identification," IEEE Conference on Robotics and Automation (ICRA) 2025. [paper][project page][code]

Chi-Hsi Kung, Chieh-Chi Yang, Pang-Yuan Pao, Shu-Wei Lu, Pin-Lun Chen, Hsin-Cheng Lu, Yi-Ting Chen, RiskBench: A Scenario-based Risk Identification Benchmark, IEEE Conference on Robotics and Automation (ICRA), 2024. [paper][Project Page][Code]

C. Li, S. H. Chan, Y.-T. Chen, "DROID: Driver-centric Risk Object Identification, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Volume: 45, Issue: 11, 01, November, 2023. [paper][IEEE]

Z. Xiao, A. Yuille, Y.-T. Chen, "Learning Road Scene-level Representations via Semantic Region Prediction," Conference on Robot Learning (CoRL), 2022. [paper]

N. Agarwal, Y.-T. Chen, "Towards Driver Behavior Understanding: Risk Perception in Driving Scenes," NeurIPS ML4AD workshop, 2022. [paper]

I. Dwivedi, S. Malla, Y.-T. Chen, and B. Dariush, "Bird’s Eye View Segmentation Using Lifted 2D Semantic Features," British Machine Vision Conference (BMVC), 2021. [paper]

C. Li,  Stanley H. Chan, and Y.-T. Chen, Who Make Drivers Stop? TowardsDriver-centric Risk Assessment: Risk Object Identification via Causal Inference, IEEE International Conference on Intelligent Robots and Systems (IROS), 2020. [paper]

M. Xu*, M. Gao*, Y.-T. Chen, L. Davis, and D. Crandall, "Temporal Recurrent Networks for Online Action Detection," IEEE International Conference on Computer Vision (ICCV), 2019. [paper][code] 

V. Ramanishka, Y.-T. Chen, T. Misu, and K. Saenko, "Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [paper][project page]

Chi-Hsi Kung, Shu-Wei Lu, Yi-Hsuan Tsai, Yi-Ting Chen, Action-Slot: Visual Action-centric Representation for Atomic Activity Recognition in Traffic Scenes, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024. [paper][Project Page][Code]

Nakul Agarwal and Yi-Ting Chen, Ordered Atomic Activity for Fine-grained Interactive Traffic Scenario Understanding, IEEE International Conference on Computer Vision (ICCV), 2023. [paper][Project Page]

N. Agarwal, Y.-T. Chen, B. Dariush, and M.-H. Yang, "Unsupervised Domain Adaptation for Spatio-Temporal Action Localization," British Machine Vision Conference (BMVC), 2020. [paper]

C. Li, Y. Meng, S. H. Chan, and Y.-T. Chen, "Learning 3D-aware Egocentric Spatial-Temporal Interaction via Graph Convolutional Networks," IEEE Conference on Robotics and Automation (ICRA), 2020. [paper]

A. Taha, Y.-T. Chen, T. Misu, A. Shrivastava, L. Davis, " Boosting Standard Classification Architectures Through a Ranking Regularizer," IEEE Winter Conference on Applications of Computer Vision (WACV), 2020. [paper][code]

A. Taha, Y.-T. Chen, X. Yang, T. Misu, and L. Davis, "Exploring Uncertainty in Conditional Multi-Modal Retrieval Systems," arXiv 1901.07702, 2019. [paper]

C.-M. Chung*, Y.-C. Tseng, Y.-C. Hsu, X.-Q. Shi, Y.-H. Hua, J.-F. Yeh, Y.-T. Chen, W.-C. Chen, Winston Hsu, "Orbeez-SLAM: A Real-time Monocular Visual SLAM with ORB Features and NeRF-realized Mapping," IEEE Conference on Robotics and Automation (ICRA), 2023. [paper][code]

J. Wang, H. Gang, S. Ancha, Y.-T. Chen, D. Held, "Semi-supervised 3D Object Detection via Temporal Graph Neural Networks," International Conference on 3D Vision (3DV), 2021. [Project Page]

J. Wang, S. Ancha, Y.-T. Chen, D. Held, "Self-supervised Learning for 3D Data Association," IEEE International Conference on Intelligent Robots and Systems (IROS), 2020. [Project Page]

A. Patil, S. Malla, H. Gang, and Y.-T. Chen, "The H3D Dataset for Full-Surround 3D Multi-Object Detection and Tracking in Crowded Urban Scenes," IEEE Conference on Robotics and Automation (ICRA), 2019. [paper][project page]

C.-Y. Wang, A. Narayanan, A. Patil, W. Zhan, and Y.-T. Chen, "A 3D Dynamic Scene Analysis Framework for Development of Intelligent Transportation Systems," IEEE Intelligent Vehicle Symposium (IV), 2018. [paper][video]