no code implementations • 22 Jan 2024 • Rusheng Zhang, Depu Meng, Shengyin Shen, Tinghan Wang, Tai Karir, Michael Maile, Henry X. Liu
This paper introduces a comprehensive evaluation methodology specifically designed to assess the performance of roadside perception systems.
no code implementations • 8 Oct 2023 • Rusheng Zhang, Depu Meng, Shengyin Shen, Zhengxia Zou, Houqiang Li, Henry X. Liu
As vehicular communication and networking technologies continue to advance, infrastructure-based roadside perception emerges as a pivotal tool for connected automated vehicle (CAV) applications.
no code implementations • 29 Jun 2023 • Rusheng Zhang, Depu Meng, Lance Bassett, Shengyin Shen, Zhengxia Zou, Henry X. Liu
Our approach was rigorously tested at two key intersections in Michigan, USA: the Mcity intersection and the State St./Ellsworth Rd roundabout.
1 code implementation • 1 Mar 2023 • Depu Meng, Owen Sayer, Rusheng Zhang, Shengyin Shen, Houqiang Li, Henry X. Liu
With the traffic conflict data collected, we discover that failure to yield to circulating vehicles when entering the roundabout is the largest contributing reason for traffic conflicts.
1 code implementation • 6 Jun 2022 • Yunsheng Ni, Depu Meng, Changqian Yu, Chengbin Quan, Dongchun Ren, Youjian Zhao
Specifically, we first capture the different representations with different augmentations, then regularize the cosine distance of the representations to enhance the consistency.
3 code implementations • ICCV 2021 • Depu Meng, Xiaokang Chen, Zejia Fan, Gang Zeng, Houqiang Li, Yuhui Yuan, Lei Sun, Jingdong Wang
Our approach, named conditional DETR, learns a conditional spatial query from the decoder embedding for decoder multi-head cross-attention.
no code implementations • 1 Jan 2021 • Depu Meng, Zigang Geng, Zhirong Wu, Bin Xiao, Houqiang Li, Jingdong Wang
The proposed consistent instance classification (ConIC) approach simultaneously optimizes the classification loss and an additional consistency loss explicitly penalizing the feature dissimilarity between the augmented views from the same instance.
1 code implementation • 28 Jun 2020 • Ke Sun, Zigang Geng, Depu Meng, Bin Xiao, Dong Liu, Zhao-Xiang Zhang, Jingdong Wang
The typical bottom-up human pose estimation framework includes two stages, keypoint detection and grouping.