SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving

no code implementations • 10 Apr 2024 • Diankun Zhang, Guoan Wang, Runwen Zhu, Jianbo Zhao, Xiwu Chen, Siyu Zhang, Jiahao Gong, Qibin Zhou, Wenyuan Zhang, Ningzi Wang, Feiyang Tan, Hangning Zhou, Ziyao Xu, Haotian Yao, Chi Zhang, Xiaojun Liu, Xiaoguang Di, Bin Li

End-to-End paradigms use a unified framework to implement multi-tasks in an autonomous driving system.

Autonomous Driving motion prediction

PillarNeSt: Embracing Backbone Scaling and Pretraining for Pillar-based 3D Object Detection

no code implementations • 29 Nov 2023 • Weixin Mao, Tiancai Wang, Diankun Zhang, Junjie Yan, Osamu Yoshie

Pillar-based methods mainly employ randomly initialized 2D convolution neural network (ConvNet) for feature extraction and fail to enjoy the benefits from the backbone scaling and pretraining in the image domain.

3D Object Detection object-detection

Structure Information is the Key: Self-Attention RoI Feature Extractor in 3D Object Detection

no code implementations • 1 Nov 2021 • Diankun Zhang, Zhijie Zheng, Xueting Bi, Xiaojun Liu

With the newly introduced SARFE, we improve the performance of the state-of-the-art 3D detectors by a large margin in cyclist on KITTI dataset while keeping real-time capability.

3D Object Detection Object +2