no code implementations • 23 Dec 2023 • Kaichen Zhou, Jia-Xing Zhong, Jia-Wang Bian, Qian Xie, Jian-Qing Zheng, Niki Trigoni, Andrew Markham
Despite advancements in self-supervised monocular depth estimation, challenges persist in dynamic scenarios due to the dependence on assumptions about a static world.
no code implementations • 29 Jan 2023 • Su Jia, Qian Xie, Nathan Kallus, Peter I. Frazier
In many applications of online decision making, the environment is non-stationary and it is therefore crucial to use bandit algorithms that handle changes.
no code implementations • 27 Jan 2023 • Qian Xie, Jiayi Wang, Li Jin
Parallel server systems in transportation, manufacturing, and computing heavily rely on dynamic routing using connected cyber components for computation and communication.
no code implementations • 21 Sep 2022 • Dening Lu, Kyle Gao, Qian Xie, Linlin Xu, Jonathan Li
This paper presents a novel point cloud representational learning network, called 3D Dual Self-attention Global Local (GLocal) Transformer Network (3DGTN), for improved feature learning in both classification and segmentation tasks, with the following key contributions.
1 code implementation • 30 Aug 2022 • Anyi Huang, Qian Xie, Zhoutao Wang, Dening Lu, Mingqiang Wei, Jun Wang
Second, a multi-scale perception module is designed to embed multi-scale geometric information for each scale feature and regress multi-scale weights to guide a multi-offset denoising displacement.
no code implementations • 16 May 2022 • Dening Lu, Qian Xie, Mingqiang Wei, Kyle Gao, Linlin Xu, Jonathan Li
To demonstrate the superiority of Transformers in point cloud analysis, we present comprehensive comparisons of various Transformer-based methods for classification, segmentation, and object detection.
no code implementations • 2 Apr 2022 • Zeyong Wei, Honghua Chen, Hao Tang, Qian Xie, Mingqiang Wei, Jun Wang
The shape of circle is one of fundamental geometric primitives of man-made engineering objects.
1 code implementation • 30 Mar 2022 • Ta-Ying Cheng, Qingyong Hu, Qian Xie, Niki Trigoni, Andrew Markham
In this work, we propose an almost-universal sampler, in our quest for a sampler that can learn to preserve the most useful points for a particular task, yet be inexpensive to adapt to different tasks, models, or datasets.
1 code implementation • 2 Mar 2022 • Dening Lu, Qian Xie, Linlin Xu, Jonathan Li
This paper presents a novel hierarchical framework that incorporates convolution with Transformer for point cloud classification, named 3D Convolution-Transformer Network (3DCTN), to combine the strong and efficient local feature learning ability of convolution with the remarkable global context modeling capability of Transformer.
no code implementations • ICCV 2021 • Qian Xie, Yu-Kun Lai, Jing Wu, Zhoutao Wang, Dening Lu, Mingqiang Wei, Jun Wang
Hough voting, as has been demonstrated in VoteNet, is effective for 3D object detection, where voting is a key step.
1 code implementation • ICCV 2021 • Zhoutao Wang, Qian Xie, Yu-Kun Lai, Jing Wu, Kun Long, Jun Wang
To deal with sparsity in outdoor 3D point clouds, we propose to perform Hough voting on multi-level features to get more vote centers and retain more useful information, instead of voting only on the final level feature as in previous methods.
1 code implementation • CVPR 2020 • Qian Xie, Yu-Kun Lai, Jing Wu, Zhoutao Wang, Yiming Zhang, Kai Xu, Jun Wang
We demonstrate these by capturing contextual information at patch, object and scene levels.
no code implementations • 9 Nov 2019 • Susan Jia Xu, Qian Xie, Joseph Y. J. Chow, Xintao Liu
In prior research, a statistically cheap method was developed to monitor transportation network performance by using only a few groups of agents without having to forecast the population flows.
no code implementations • 14 Oct 2016 • Hamid Laga, Qian Xie, Ian H. Jermyn, Anuj Srivastava
Recent developments in elastic shape analysis (ESA) are motivated by the fact that it provides comprehensive frameworks for simultaneous registration, deformation, and comparison of shapes.