96 citations · 137 across the 6 of their papers we have counts for
6 papers
AFDetV2: Rethinking the Necessity of the Second Stage for Object Detection from Point Clouds
Yihan Hu, Zhuangzhuang Ding, Runzhou Ge +4
There have been two streams in the 3D detection from point clouds: single-stage methods and two-stage methods. While the former is more computationally efficient, the latter usuall…
Real-Time Anchor-Free Single-Stage 3D Detection with IoU-Awareness
Runzhou Ge, Zhuangzhuang Ding, Yihan Hu +4
In this report, we introduce our winning solution to the Real-time 3D Detection and also the "Most Efficient Model" in the Waymo Open Dataset Challenges at CVPR 2021. Extended from…
AFDet: Anchor Free One Stage 3D Object Detection
Runzhou Ge, Zhuangzhuang Ding, Yihan Hu +4
High-efficiency point cloud 3D object detection operated on embedded systems is important for many robotics applications including autonomous driving. Most previous works try to so…
2nd Place Solution for Waymo Open Dataset Challenge -- 2D Object Detection
Sijia Chen, Yu Wang, Li Huang +4
A practical autonomous driving system urges the need to reliably and accurately detect vehicles and persons. In this report, we introduce a state-of-the-art 2D object detection sys…
1st Place Solutions for Waymo Open Dataset Challenges -- 2D and 3D Tracking
Yu Wang, Sijia Chen, Li Huang +4
This technical report presents the online and real-time 2D and 3D multi-object tracking (MOT) algorithms that reached the 1st places on both Waymo Open Dataset 2D tracking and 3D t…
1st Place Solution for Waymo Open Dataset Challenge -- 3D Detection and Domain Adaptation
Zhuangzhuang Ding, Yihan Hu, Runzhou Ge +4
In this technical report, we introduce our winning solution "HorizonLiDAR3D" for the 3D detection track and the domain adaptation track in Waymo Open Dataset Challenge at CVPR 2020…