1 code implementation • 19 Sep 2023 • Xiangchao Yan, Runjian Chen, Bo Zhang, Jiakang Yuan, Xinyu Cai, Botian Shi, Wenqi Shao, Junchi Yan, Ping Luo, Yu Qiao
Our contributions are threefold: (1) Occupancy prediction is shown to be promising for learning general representations, which is demonstrated by extensive experiments on plenty of datasets and tasks.
2 code implementations • 11 Sep 2023 • Bo Zhang, Xinyu Cai, Jiakang Yuan, Donglin Yang, Jianfei Guo, Xiangchao Yan, Renqiu Xia, Botian Shi, Min Dou, Tao Chen, Si Liu, Junchi Yan, Yu Qiao
Domain shifts such as sensor type changes and geographical situation variations are prevalent in Autonomous Driving (AD), which poses a challenge since AD model relying on the previous domain knowledge can be hardly directly deployed to a new domain without additional costs.
1 code implementation • NeurIPS 2023 • Jiakang Yuan, Bo Zhang, Xiangchao Yan, Tao Chen, Botian Shi, Yikang Li, Yu Qiao
It is a long-term vision for Autonomous Driving (AD) community that the perception models can learn from a large-scale point cloud dataset, to obtain unified representations that can achieve promising results on different tasks or benchmarks.
1 code implementation • CVPR 2023 • Bo Zhang, Jiakang Yuan, Botian Shi, Tao Chen, Yikang Li, Yu Qiao
In this paper, we study the task of training a unified 3D detector from multiple datasets.
1 code implementation • CVPR 2023 • Jiakang Yuan, Bo Zhang, Xiangchao Yan, Tao Chen, Botian Shi, Yikang Li, Yu Qiao
Unsupervised Domain Adaptation (UDA) technique has been explored in 3D cross-domain tasks recently.
1 code implementation • 20 Dec 2022 • Ben Fei, Siyuan Huang, Jiakang Yuan, Botian Shi, Bo Zhang, Weidong Yang, Min Dou, Yikang Li
Different from previous studies that only focus on a single adaptation task, UniDA3D can tackle several adaptation tasks in 3D segmentation field, by designing a unified source-and-target active sampling strategy, which selects a maximally-informative subset from both source and target domains for effective model adaptation.
1 code implementation • 2 Jul 2022 • Bo Zhang, Jiakang Yuan, Baopu Li, Tao Chen, Jiayuan Fan, Botian Shi
Few-shot fine-grained learning aims to classify a query image into one of a set of support categories with fine-grained differences.