5 papers
Explainability-Aware Frustum Attack: Exposing Structural Vulnerabilities in LiDAR-Based 3D Object Detectors
Chengzeng You, Binbin Xu, Soteris Demetriou
The structural vulnerabilities of point cloud-based 3D object detectors remain poorly understood. Prior work has studied adversarial robustness primarily on isolated 3D object mode…
UnPose: Uncertainty-Guided Diffusion Priors for Zero-Shot Pose Estimation
Zhaodong Jiang, Ashish Sinha, Tongtong Cao +3
Estimating the 6D pose of novel objects is a fundamental yet challenging problem in robotics, often relying on access to object CAD models. However, acquiring such models can be co…
HIPPo: Harnessing Image-to-3D Priors for Model-free Zero-shot 6D Pose Estimation
Yibo Liu, Zhaodong Jiang, Binbin Xu +7
This work focuses on model-free zero-shot 6D object pose estimation for robotics applications. While existing methods can estimate the precise 6D pose of objects, they heavily rely…
Toward General Object-level Mapping from Sparse Views with 3D Diffusion Priors
Ziwei Liao, Binbin Xu, Steven L. Waslander
Object-level mapping builds a 3D map of objects in a scene with detailed shapes and poses from multi-view sensor observations. Conventional methods struggle to build complete shape…
Adversarial 3D Virtual Patches using Integrated Gradients
Chengzeng You, Zhongyuan Hau, Binbin Xu +1
LiDAR sensors are widely used in autonomous vehicles to better perceive the environment. However, prior works have shown that LiDAR signals can be spoofed to hide real objects from…