226 citations · 302 across the 8 of their papers we have counts for
9 papers
AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection
Zongdai Liu, Dingfu Zhou, Feixiang Lu +2
Existing deep learning-based approaches for monocular 3D object detection in autonomous driving often model the object as a rotated 3D cuboid while the object's geometric shape has…
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks
Yulong Cao*, Ningfei Wang*, Chaowei Xiao* +6
In Autonomous Driving (AD) systems, perception is both security and safety critical. Despite various prior studies on its security issues, all of them only consider attacks on came…
FusionPainting: Multimodal Fusion with Adaptive Attention for 3D Object Detection
Shaoqing Xu, Dingfu Zhou, Jin Fang +3
Accurate detection of obstacles in 3D is an essential task for autonomous driving and intelligent transportation. In this work, we propose a general multimodal fusion framework Fus…
Large Scale Autonomous Driving Scenarios Clustering with Self-supervised Feature Extraction
Jinxin Zhao, Jin Fang, Zhixian Ye +1
The clustering of autonomous driving scenario data can substantially benefit the autonomous driving validation and simulation systems by improving the simulation tests' completenes…
MapFusion: A General Framework for 3D Object Detection with HDMaps
Jin Fang, Dingfu Zhou, Xibin Song +1
3D object detection is a key perception component in autonomous driving. Most recent approaches are based on Lidar sensors only or fused with cameras. Maps (e.g., High Definition M…
IAFA: Instance-aware Feature Aggregation for 3D Object Detection from a Single Image
Dingfu Zhou, Xibin Song, Yuchao Dai +5
3D object detection from a single image is an important task in Autonomous Driving (AD), where various approaches have been proposed. However, the task is intrinsically ambiguous a…