1 citations · 1 across the 13 of their papers we have counts for
14 papers
GaussianMap: Learning Gaussian Representation for Multi-Sensor Online HD Map Construction
Hongyu Lyu, Julie Stephany Berrio Perez, Mao Shan +1
Autonomous driving systems benefit from high-definition (HD) maps that provide critical information about road infrastructure. The online construction of HD maps offers a scalable…
Hazard-Aware Traffic Scene Graph Generation
Yaoqi Huang, Julie Stephany Berrio, Mao Shan +1
Maintaining situational awareness in complex driving scenarios is challenging. It requires continuously prioritizing attention among extensive scene entities and understanding how…
TFusionOcc: T-Primitive Based Object-Centric Multi-Sensor Fusion Framework for 3D Occupancy Prediction
Zhenxing Ming, Yaoqi Huang, Julie Stephany Berrio +2
The prediction of 3D semantic occupancy enables autonomous vehicles (AVs) to perceive the fine-grained geometric and semantic scene structure for safe navigation and decision-makin…
Data Augmentation Strategies for Robust Lane Marking Detection
Flora Lian, Dinh Quang Huynh, Hector Penades +3
Robust lane detection is essential for advanced driver assistance and autonomous driving, yet models trained on public datasets such as CULane often fail to generalise across diffe…
MapRF: Weakly Supervised Online HD Map Construction via NeRF-Guided Self-Training
Hongyu Lyu, Thomas Monninger, Julie Stephany Berrio Perez +3
Autonomous driving systems benefit from high-definition (HD) maps that provide critical information about road infrastructure. The online construction of HD maps offers a scalable…
InterKey: Cross-modal Intersection Keypoints for Global Localization on OpenStreetMap
Nguyen Hoang Khoi Tran, Julie Stephany Berrio, Mao Shan +1
Reliable global localization is critical for autonomous vehicles, especially in environments where GNSS is degraded or unavailable, such as urban canyons and tunnels. Although high…
Multi-Modal Camera-Based Detection of Vulnerable Road Users
Penelope Brown, Julie Stephany Berrio Perez, Mao Shan +1
Vulnerable road users (VRUs) such as pedestrians, cyclists, and motorcyclists represent more than half of global traffic deaths, yet their detection remains challenging in poor lig…
Towards Adaptive External Communication in Autonomous Vehicles: A Conceptual Design Framework
Tram Thi Minh Tran, Judy Kay, Stewart Worrall +6
External Human-Machine Interfaces (eHMIs) are key to facilitating interaction between autonomous vehicles and external road actors, yet most remain reactive and do not account for…
OccCylindrical: Multi-Modal Fusion with Cylindrical Representation for 3D Semantic Occupancy Prediction
Zhenxing Ming, Julie Stephany Berrio, Mao Shan +5
The safe operation of autonomous vehicles (AVs) is highly dependent on their understanding of the surroundings. For this, the task of 3D semantic occupancy prediction divides the s…
InterLoc: LiDAR-based Intersection Localization using Road Segmentation with Automated Evaluation Method
Nguyen Hoang Khoi Tran, Julie Stephany Berrio, Mao Shan +2
Online localization of road intersections is beneficial for autonomous vehicle localization, mapping and motion planning. Intersections offer strong landmarks for correcting vehicl…
M2S-RoAD: Multi-Modal Semantic Segmentation for Road Damage Using Camera and LiDAR Data
Tzu-Yun Tseng, Hongyu Lyu, Josephine Li +3
Road damage can create safety and comfort challenges for both human drivers and autonomous vehicles (AVs). This damage is particularly prevalent in rural areas due to less frequent…
SydneyScapes: Image Segmentation for Australian Environments
Hongyu Lyu, Julie Stephany Berrio, Mao Shan +1
Autonomous Vehicles (AVs) are being partially deployed and tested across various global locations, including China, the USA, Germany, France, Japan, Korea, and the UK, but with lim…
Panoptic-CUDAL: Rural Australia Point Cloud Dataset in Rainy Conditions
Tzu-Yun Tseng, Alexey Nekrasov, Malcolm Burdorf +5
Existing autonomous driving datasets are predominantly oriented towards well-structured urban settings and favourable weather conditions, leaving the complexities of rural environm…
Mixed Signals: A Diverse Point Cloud Dataset for Heterogeneous LiDAR V2X Collaboration
Katie Z Luo, Minh-Quan Dao, Zhenzhen Liu +9
Vehicle-to-everything (V2X) collaborative perception has emerged as a promising solution to address the limitations of single-vehicle perception systems. However, existing V2X data…