8 citations · 23 across the 12 of their papers we have counts for
13 papers
TLP: A Deep Learning-based Cost Model for Tensor Program Tuning
Yi Zhai, Yu Zhang, Shuo Liu +4
Tensor program tuning is a non-convex objective optimization problem, to which search-based approaches have proven to be effective. At the core of the search-based approaches lies…
MAROAM: Map-based Radar SLAM through Two-step Feature Selection
Dequan Wang, Yifan Duan, Xiaoran Fan +3
In this letter, we propose MAROAM, a millimeter wave radar-based SLAM framework, which employs a two-step feature selection process to build the global consistent map. Specifically…
Crowd-Aware Robot Navigation for Pedestrians with Multiple Collision Avoidance Strategies via Map-based Deep Reinforcement Learning
Shunyi Yao1, Guangda Chen, Quecheng Qiu +3
It is challenging for a mobile robot to navigate through human crowds. Existing approaches usually assume that pedestrians follow a predefined collision avoidance strategy, like so…
DRQN-based 3D Obstacle Avoidance with a Limited Field of View
Yu'an Chen, Guangda Chen, Lifan Pan +4
In this paper, we propose a map-based end-to-end DRL approach for three-dimensional (3D) obstacle avoidance in a partially observed environment, which is applied to achieve autonom…
Neighbor-Vote: Improving Monocular 3D Object Detection through Neighbor Distance Voting
Xiaomeng Chu, Jiajun Deng, Yao Li +4
As cameras are increasingly deployed in new application domains such as autonomous driving, performing 3D object detection on monocular images becomes an important task for visual…
3D Segmentation Learning from Sparse Annotations and Hierarchical Descriptors
Peng Yin, Lingyun Xu, Jianmin Ji +2
One of the main obstacles to 3D semantic segmentation is the significant amount of endeavor required to generate expensive point-wise annotations for fully supervised training. To…