no code implementations • AAAI workshop 2024 • Boxiang Zhang, Baijian Yang, Xiaoming Wang, Corey Vian
Our method illustrates the potential of leveraging computer vision and deep learning techniques to advance inspection capabilities for the die casting industry.
no code implementations • 9 Jul 2023 • Boxiang Zhang, Zunran Wang, Yonggen Ling, Yuanyuan Guan, Shenghao Zhang, Wenhui Li
Existing methods of cross-modal domain adaptation for 3D semantic segmentation predict results only via 2D-3D complementarity that is obtained by cross-modal feature matching.
no code implementations • 6 Nov 2021 • Shaoxiu Wei, Boxiang Zhang, Wei Yi
These filters are referred to as the unknown TPHD (U-TPHD) and unknown TCPHD (U-TCPHD) filters. By minimizing the Kullback-Leibler divergence (KLD), the U-TPHD and U-TCPHD filters can obtain, respectively, the best Poisson and independent identically distributed (IID) density approximations over the augmented sets of trajectories.
no code implementations • 6 Nov 2021 • Shaoxiu Wei, Boxiang Zhang, Wei Yi
To account for joint tracking and classification (JTC) of multiple targets from observation sets in presence of detection uncertainty, noise and clutter, this paper develops a new trajectory probability hypothesis density (TPHD) filter, which is referred to as the JTC-TPHD filter.
no code implementations • 6 Nov 2021 • Shaoxiu Wei, Boxiang Zhang, Wei Yi
Because of the huge computational burden and the short-term stability of the detection profile, we also propose the R-TPHD filter with unknown detection profile only at current time as an approximation.
no code implementations • 10 Aug 2020 • Boxiang Zhang, Wei Yi
Firstly, we extend the concept of JMS to the multi-trajectory scenario of maneuvering target and derive the TPHD recursion for the proposed JMS model.