99 citations · 104 across the 5 of their papers we have counts for
8 papers
Viewer-Centred Surface Completion for Unsupervised Domain Adaptation in 3D Object Detection
Darren Tsai, Julie Stephany Berrio, Mao Shan +2
Every autonomous driving dataset has a different configuration of sensors, originating from distinct geographic regions and covering various scenarios. As a result, 3D detectors te…
What is the appropriate speed for an autonomous vehicle? Designing a Pedestrian Aware Contextual Speed Controller
Daniel Jiang, Stewart Worrall, Mao Shan
Social acceptance is a major hurdle for autonomous vehicle technology, central to which is ensuring both passengers and nearby pedestrians feel safe. This idea of `feeling safe' an…
Optimising the selection of samples for robust lidar camera calibration
Darren Tsai, Stewart Worrall, Mao Shan +2
We propose a robust calibration pipeline that optimises the selection of calibration samples for the estimation of calibration parameters that fit the entire scene. We minimise use…
Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations
Mao Shan, Karan Narula, Yung Fei Wong +4
Cooperative perception, or collective perception (CP) is an emerging and promising technology for intelligent transportation systems (ITS). It enables an ITS station (ITS-S) to sha…
Long-term map maintenance pipeline for autonomous vehicles
Julie Stephany Berrio, Stewart Worrall, Mao Shan +1
For autonomous vehicles to operate persistently in a typical urban environment, it is essential to have high accuracy position information. This requires a mapping and localisation…
Probabilistic Crowd GAN: Multimodal Pedestrian Trajectory Prediction using a Graph Vehicle-Pedestrian Attention Network
Stuart Eiffert, Kunming Li, Mao Shan +3
Understanding and predicting the intention of pedestrians is essential to enable autonomous vehicles and mobile robots to navigate crowds. This problem becomes increasingly complex…