53 citations · 149 across the 12 of their papers we have counts for
12 papers
Influence of Camera-LiDAR Configuration on 3D Object Detection for Autonomous Driving
Ye Li, Hanjiang Hu, Zuxin Liu +3
Cameras and LiDARs are both important sensors for autonomous driving, playing critical roles in 3D object detection. Camera-LiDAR Fusion has been a prevalent solution for robust an…
Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations
Hanjiang Hu, Zuxin Liu, Linyi Li +2
Deep learning-based visual perception models lack robustness when faced with camera motion perturbations in practice. The current certification process for assessing robustness is…
The RoboDepth Challenge: Methods and Advancements Towards Robust Depth Estimation
Lingdong Kong, Yaru Niu, Shaoyuan Xie +39
Accurate depth estimation under out-of-distribution (OoD) scenarios, such as adverse weather conditions, sensor failure, and noise contamination, is desirable for safety-critical a…
Datasets and Benchmarks for Offline Safe Reinforcement Learning
Zuxin Liu, Zijian Guo, Haohong Lin +8
This paper presents a comprehensive benchmarking suite tailored to offline safe reinforcement learning (RL) challenges, aiming to foster progress in the development and evaluation…
Robustness Certification of Visual Perception Models via Camera Motion Smoothing
Hanjiang Hu, Zuxin Liu, Linyi Li +2
A vast literature shows that the learning-based visual perception model is sensitive to adversarial noises, but few works consider the robustness of robotic perception models under…
SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles
Chejian Xu, Wenhao Ding, Weijie Lyu +6
As shown by recent studies, machine intelligence-enabled systems are vulnerable to test cases resulting from either adversarial manipulation or natural distribution shifts. This ha…
Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous Driving
Hanjiang Hu, Zuxin Liu, Sharad Chitlangia +2
The past few years have witnessed an increasing interest in improving the perception performance of LiDARs on autonomous vehicles. While most of the existing works focus on develop…
A Registration-aided Domain Adaptation Network for 3D Point Cloud Based Place Recognition
Zhijian Qiao, Hanjiang Hu, Weiang Shi +3
In the field of large-scale SLAM for autonomous driving and mobile robotics, 3D point cloud based place recognition has aroused significant research interest due to its robustness…
DASGIL: Domain Adaptation for Semantic and Geometric-aware Image-based Localization
Hanjiang Hu, Zhijian Qiao, Ming Cheng +2
Long-Term visual localization under changing environments is a challenging problem in autonomous driving and mobile robotics due to season, illumination variance, etc. Image retrie…
SeasonDepth: Cross-Season Monocular Depth Prediction Dataset and Benchmark under Multiple Environments
Hanjiang Hu, Baoquan Yang, Zhijian Qiao +6
Different environments pose a great challenge to the outdoor robust visual perception for long-term autonomous driving, and the generalization of learning-based algorithms on diffe…
Domain-invariant Similarity Activation Map Contrastive Learning for Retrieval-based Long-term Visual Localization
Hanjiang Hu, Hesheng Wang, Zhe Liu +1
Visual localization is a crucial component in the application of mobile robot and autonomous driving. Image retrieval is an efficient and effective technique in image-based localiz…
Retrieval-based Localization Based on Domain-invariant Feature Learning under Changing Environments
Hanjiang Hu, Hesheng Wang, Zhe Liu +3
Visual localization is a crucial problem in mobile robotics and autonomous driving. One solution is to retrieve images with known pose from a database for the localization of query…