5 papers
Ghost-FWL: A Large-Scale Full-Waveform LiDAR Dataset for Ghost Detection and Removal
Kazuma Ikeda, Ryosei Hara, Rokuto Nagata +6
LiDAR has become an essential sensing modality in autonomous driving, robotics, and smart-city applications. However, ghost points (or ghosts), which are false reflections caused b…
D-SLAMSpoof: An Environment-Agnostic LiDAR Spoofing Attack using Dynamic Point Cloud Injection
Rokuto Nagata, Kenji Koide, Kazuma Ikeda +2
In this work, we introduce Dynamic SLAMSpoof (D-SLAMSpoof), a novel attack that compromises LiDAR SLAM even in feature-rich environments. The attack leverages LiDAR spoofing, which…
MirrorDrift: Actuated Mirror-Based Attacks on LiDAR SLAM
Rokuto Nagata, Kenji Koide, Kazuma Ikeda +3
LiDAR SLAM provides high-accuracy localization but is fragile to point-cloud corruption because scan matching assumes geometric consistency. Prior physical attacks on LiDAR SLAM la…
BasketLiDAR: The First LiDAR-Camera Multimodal Dataset for Professional Basketball MOT
Ryunosuke Hayashi, Kohei Torimi, Rokuto Nagata +6
Real-time 3D trajectory player tracking in sports plays a crucial role in tactical analysis, performance evaluation, and enhancing spectator experience. Traditional systems rely on…
SLAMSpoof: Practical LiDAR Spoofing Attacks on Localization Systems Guided by Scan Matching Vulnerability Analysis
Rokuto Nagata, Kenji Koide, Yuki Hayakawa +6
Accurate localization is essential for enabling modern full self-driving services. These services heavily rely on map-based traffic information to reduce uncertainties in recognizi…