12 citations · 19 across the 4 of their papers we have counts for
4 papers
CoFF: Cooperative Spatial Feature Fusion for 3D Object Detection on Autonomous Vehicles
Jingda Guo, Dominic Carrillo, Sihai Tang +6
To reduce the amount of transmitted data, feature map based fusion is recently proposed as a practical solution to cooperative 3D object detection by autonomous vehicles. The preci…
DCANet: Learning Connected Attentions for Convolutional Neural Networks
Xu Ma, Jingda Guo, Sihai Tang +4
While self-attention mechanism has shown promising results for many vision tasks, it only considers the current features at a time. We show that such a manner cannot take full adva…
Low-Latency High-Level Data Sharing for Connected and Autonomous Vehicular Networks
Qi Chen, Sihai Tang, Jacob Hochstetler +5
Autonomous vehicles can combine their own data with that of other vehicles to enhance their perceptive ability, and thus improve detection accuracy and driving safety. Data sharing…
Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds
Qi Chen, Sihai Tang, Qing Yang +1
Autonomous vehicles may make wrong decisions due to inaccurate detection and recognition. Therefore, an intelligent vehicle can combine its own data with that of other vehicles to…