Abstract: Traditional 3D Convolutional Neural Networks (CNNs) are computationally expensive, memory intensive, prone to overfit, and most importantly, there is a need to improve their feature learning ...

We present our on-line tracking method, which wins the first place award of the NuScenes Tracking Challenge[1], held in the AI Driving Olympics Workshop at NeurIPS 2019. Our technical report is ...

Abstract: For several years, the reconstruction of Computer Aided Design (CAD) models from a deformed mesh get more and more attention. This CAD model is used in order to visualize 3D objects that ...