4 citations · 5 across the 11 of their papers we have counts for
13 papers
What Demands Attention in Urban Street Scenes? From Scene Understanding towards Road Safety: A Survey of Vision-driven Datasets and Studies
Yaoqi Huang, Julie Stephany Berrio, Mao Shan +1
Advances in vision-based sensors and computer vision algorithms have significantly improved the analysis and understanding of traffic scenarios. To facilitate the use of these impr…
Inverse++: Vision-Centric 3D Semantic Occupancy Prediction Assisted with 3D Object Detection
Zhenxing Ming, Julie Stephany Berrio, Mao Shan +1
3D semantic occupancy prediction aims to forecast detailed geometric and semantic information of the surrounding environment for autonomous vehicles (AVs) using onboard surround-vi…
Endangered Alert: A Field-Validated Self-Training Scheme for Detecting and Protecting Threatened Wildlife on Roads and Roadsides
Kunming Li, Mao Shan, Stephany Berrio Perez +2
Traffic accidents are a global safety concern, resulting in numerous fatalities each year. A considerable number of these deaths are caused by animal-vehicle collisions (AVCs), whi…
Label-Efficient 3D Object Detection For Road-Side Units
Minh-Quan Dao, Holger Caesar, Julie Stephany Berrio +4
Occlusion presents a significant challenge for safety-critical applications such as autonomous driving. Collaborative perception has recently attracted a large research interest th…
OccFusion: Multi-Sensor Fusion Framework for 3D Semantic Occupancy Prediction
Zhenxing Ming, Julie Stephany Berrio, Mao Shan +1
A comprehensive understanding of 3D scenes is crucial in autonomous vehicles (AVs), and recent models for 3D semantic occupancy prediction have successfully addressed the challenge…
InverseMatrixVT3D: An Efficient Projection Matrix-Based Approach for 3D Occupancy Prediction
Zhenxing Ming, Julie Stephany Berrio, Mao Shan +1
This paper introduces InverseMatrixVT3D, an efficient method for transforming multi-view image features into 3D feature volumes for 3D semantic occupancy prediction. Existing metho…
Classification of Safety Driver Attention During Autonomous Vehicle Operation
Santiago Gerling Konrad, Julie Stephany Berrio, Mao Shan +2
Despite the continual advances in Advanced Driver Assistance Systems (ADAS) and the development of high-level autonomous vehicles (AV), there is a general consensus that for the sh…
LightFormer: An End-to-End Model for Intersection Right-of-Way Recognition Using Traffic Light Signals and an Attention Mechanism
Zhenxing Ming, Julie Stephany Berrio, Mao Shan +2
For smart vehicles driving through signalised intersections, it is crucial to determine whether the vehicle has right of way given the state of the traffic lights. To address this…
Practical Collaborative Perception: A Framework for Asynchronous and Multi-Agent 3D Object Detection
Minh-Quan Dao, Julie Stephany Berrio, Vincent Frémont +3
Occlusion is a major challenge for LiDAR-based object detection methods. This challenge becomes safety-critical in urban traffic where the ego vehicle must have reliable object det…
A Novel Probabilistic V2X Data Fusion Framework for Cooperative Perception
Mao Shan, Karan Narula, Stewart Worrall +4
The paper addresses the vehicle-to-X (V2X) data fusion for cooperative or collective perception (CP). This emerging and promising intelligent transportation systems (ITS) technolog…
Socially Aware Crowd Navigation with Multimodal Pedestrian Trajectory Prediction for Autonomous Vehicles
Kunming Li, Mao Shan, Karan Narula +2
Seamlessly operating an autonomous vehicle in a crowded pedestrian environment is a very challenging task. This is because human movement and interactions are very hard to predict…
Attentional-GCNN: Adaptive Pedestrian Trajectory Prediction towards Generic Autonomous Vehicle Use Cases
Kunming Li, Stuart Eiffert, Mao Shan +3
Autonomous vehicle navigation in shared pedestrian environments requires the ability to predict future crowd motion both accurately and with minimal delay. Understanding the uncert…
Semantic sensor fusion: from camera to sparse lidar information
Julie Stephany Berrio, Mao Shan, Stewart Worrall +2
To navigate through urban roads, an automated vehicle must be able to perceive and recognize objects in a three-dimensional environment. A high-level contextual understanding of th…