activity
20162026
most citedInvisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks

226 citations · 667 across the 29 of their papers we have counts for

collaborators
Showing 2018Show all

16 papers · 1 filter

cs.GR2018

Heter-Sim: Heterogeneous multi-agent systems simulation by interactive data-driven optimization

Jiaping Ren, Wei Xiang, Yangxi Xiao +3

Interactive multi-agent simulation algorithms are used to compute the trajectories and behaviors of different entities in virtual reality scenarios. However, current methods involv…

cs.CV2018

ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving

Xibin Song, Peng Wang, Dingfu Zhou +6

Autonomous driving has attracted remarkable attention from both industry and academia. An important task is to estimate 3D properties(e.g.translation, rotation and shape) of a movi…

cs.CV2018

Part-level Car Parsing and Reconstruction from Single Street View

Qichuan Geng, Hong Zhang, Xinyu Huang +5

Part information has been shown to be resistant to occlusions and viewpoint changes, which is beneficial for various vision-related tasks. However, we found very limited work in ca…

cs.CV2018

Augmented LiDAR Simulator for Autonomous Driving

Jin Fang, Dingfu Zhou, Feilong Yan +5

In Autonomous Driving (AD), detection and tracking of obstacles on the roads is a critical task. Deep-learning based methods using annotated LiDAR data have been the most widely ad…

cs.CV2018

TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agents

Yuexin Ma, Xinge Zhu, Sibo Zhang +3

To safely and efficiently navigate in complex urban traffic, autonomous vehicles must make responsible predictions in relation to surrounding traffic-agents (vehicles, bicycles, pe…

cs.CV2018

Learning Depth with Convolutional Spatial Propagation Network

Xinjing Cheng, Peng Wang, Ruigang Yang

Depth prediction is one of the fundamental problems in computer vision. In this paper, we propose a simple yet effective convolutional spatial propagation network (CSPN) to learn t…