10 citations · 14 across the 6 of their papers we have counts for
6 papers
3D Object Visibility Prediction in Autonomous Driving
Chuanyu Luo, Nuo Cheng, Ren Zhong +4
With the rapid advancement of hardware and software technologies, research in autonomous driving has seen significant growth. The prevailing framework for multi-sensor autonomous d…
Mini-PointNetPlus: a local feature descriptor in deep learning model for 3d environment perception
Chuanyu Luo, Nuo Cheng, Sikun Ma +4
Common deep learning models for 3D environment perception often use pillarization/voxelization methods to convert point cloud data into pillars/voxels and then process it with a 2D…
LEST: Large-scale LiDAR Semantic Segmentation with Transformer
Chuanyu Luo, Nuo Cheng, Sikun Ma +4
Large-scale LiDAR-based point cloud semantic segmentation is a critical task in autonomous driving perception. Almost all of the previous state-of-the-art LiDAR semantic segmentati…
MVP-Net: Multiple View Pointwise Semantic Segmentation of Large-Scale Point Clouds
Chuanyu Luo, Xiaohan Li, Nuo Cheng +3
Semantic segmentation of 3D point cloud is an essential task for autonomous driving environment perception. The pipeline of most pointwise point cloud semantic segmentation methods…
FenceMask: A Data Augmentation Approach for Pre-extracted Image Features
Pu Li, Xiangyang Li, Xiang Long
We propose a novel data augmentation method named 'FenceMask' that exhibits outstanding performance in various computer vision tasks. It is based on the 'simulation of object occlu…
Review of Text Style Transfer Based on Deep Learning
Xiangyang Li, Guo Pu, Keyu Ming +3
Text style transfer is a hot issue in recent natural language processing,which mainly studies the text to adapt to different specific situations, audiences and purposes by making s…