1 citations · 2 across the 2 of their papers we have counts for
5 papers
LiSnowNet: Real-time Snow Removal for LiDAR Point Cloud
Ming-Yuan Yu, Ram Vasudevan, Matthew Johnson-Roberson
LiDARs have been widely adopted to modern self-driving vehicles, providing 3D information of the scene and surrounding objects. However, adverser weather conditions still pose sign…
Learning Rotation-Invariant Representations of Point Clouds Using Aligned Edge Convolutional Neural Networks
Junming Zhang, Ming-Yuan Yu, Ram Vasudevan +1
Point cloud analysis is an area of increasing interest due to the development of 3D sensors that are able to rapidly measure the depth of scenes accurately. Unfortunately, applying…
Risk Assessment and Planning with Bidirectional Reachability for Autonomous Driving
Ming-Yuan Yu, Ram Vasudevan, Matthew Johnson-Roberson
Knowing and predicting dangerous factors within a scene are two key components during autonomous driving, especially in a crowded urban environment. To navigate safely in environme…
PedX: Benchmark Dataset for Metric 3D Pose Estimation of Pedestrians in Complex Urban Intersections
Wonhui Kim, Manikandasriram Srinivasan Ramanagopal, Charles Barto +5
This paper presents a novel dataset titled PedX, a large-scale multimodal collection of pedestrians at complex urban intersections. PedX consists of more than 5,000 pairs of high-r…
Occlusion-Aware Risk Assessment for Autonomous Driving in Urban Environments
Ming-Yuan Yu, Ram Vasudevan, Matthew Johnson-Roberson
Navigating safely in urban environments remains a challenging problem for autonomous vehicles. Occlusion and limited sensor range can pose significant challenges to safely navigate…