output
20192022
most citedInvisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks

226 citations

10 papers

cs.CV20228 cited

A Representation Separation Perspective to Correspondences-free Unsupervised 3D Point Cloud Registration

Zhiyuan Zhang, Jiadai Sun, Yuchao Dai +3

3D point cloud registration in remote sensing field has been greatly advanced by deep learning based methods, where the rigid transformation is either directly regressed from the t…

cs.CR2021226 cited

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…

cs.CV2021

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…

cs.IR20216 cited

Spatial Object Recommendation with Hints: When Spatial Granularity Matters

Hui Luo, Jingbo Zhou, Zhifeng Bao +5

Existing spatial object recommendation algorithms generally treat objects identically when ranking them. However, spatial objects often cover different levels of spatial granularit…

cs.SE20207 cited

Intelligent Exploration for User Interface Modules of Mobile App with Collective Learning

Jingbo Zhou, Zhenwei Tang, Min Zhao +6

A mobile app interface usually consists of a set of user interface modules. How to properly design these user interface modules is vital to achieving user satisfaction for a mobile…

cs.CV20207 cited

Channel Attention based Iterative Residual Learning for Depth Map Super-Resolution

Xibin Song, Yuchao Dai, Dingfu Zhou +4

Despite the remarkable progresses made in deep-learning based depth map super-resolution (DSR), how to tackle real-world degradation in low-resolution (LR) depth maps remains a maj…