The paper contributes an open-source benchmark framework and evaluation protocol for physical adversarial object attacks against LiDAR detection, with systematic loss and hyperparameter ablations and a sim-to-real demonstration.
KITTI-CARLA: a KITTI-like dataset generated by CARLA Simulator
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abstract
KITTI-CARLA is a dataset built from the CARLA v0.9.10 simulator using a vehicle with sensors identical to the KITTI dataset. The vehicle thus has a Velodyne HDL64 LiDAR positioned in the middle of the roof and two color cameras similar to Point Grey Flea 2. The positions of the LiDAR and cameras are the same as the setup used in KITTI. The objective of this dataset is to test approaches of semantic segmentation LiDAR and/or images, odometry LiDAR and/or image in synthetic data and to compare with the results obtained on real data like KITTI. This dataset thus makes it possible to improve transfer learning methods from a synthetic dataset to a real dataset. We created 7 sequences with 5000 frames in each sequence in the 7 maps of CARLA providing different environments (city, suburban area, mountain, rural area, highway...). The dataset is available at: http://npm3d.fr
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Revisiting Physically Realizable Adversarial Object Attack against LiDAR-based Detection: Clarifying Problem Formulation and Experimental Protocols
The paper contributes an open-source benchmark framework and evaluation protocol for physical adversarial object attacks against LiDAR detection, with systematic loss and hyperparameter ablations and a sim-to-real demonstration.