14 citations · 31 across the 6 of their papers we have counts for
5 papers · 1 filter
FOMO-3D: Using Vision Foundation Models for Long-Tailed 3D Object Detection
Anqi Joyce Yang, James Tu, Nikita Dvornik +2
In order to navigate complex traffic environments, self-driving vehicles must recognize many semantic classes pertaining to vulnerable road users or traffic control devices. Howeve…
StrObe: Streaming Object Detection from LiDAR Packets
Davi Frossard, Simon Suo, Sergio Casas +3
Many modern robotics systems employ LiDAR as their main sensing modality due to its geometrical richness. Rolling shutter LiDARs are particularly common, in which an array of laser…
Learning to Communicate and Correct Pose Errors
Nicholas Vadivelu, Mengye Ren, James Tu +2
Learned communication makes multi-agent systems more effective by aggregating distributed information. However, it also exposes individual agents to the threat of erroneous message…
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction
Tsun-Hsuan Wang, Sivabalan Manivasagam, Ming Liang +4
In this paper, we explore the use of vehicle-to-vehicle (V2V) communication to improve the perception and motion forecasting performance of self-driving vehicles. By intelligently…
Physically Realizable Adversarial Examples for LiDAR Object Detection
James Tu, Mengye Ren, Siva Manivasagam +5
Modern autonomous driving systems rely heavily on deep learning models to process point cloud sensory data; meanwhile, deep models have been shown to be susceptible to adversarial…