5 papers
SA-MLP: A Low-Power Multiplication-Free Deep Network for 3D Point Cloud Classification in Resource-Constrained Environments
Qiang Zheng, Chao Zhang, Jian Sun
Point cloud classification plays a crucial role in the processing and analysis of data from 3D sensors such as LiDAR, which are commonly used in applications like autonomous vehicl…
Efficient Point Cloud Classification via Offline Distillation Framework and Negative-Weight Self-Distillation Technique
Qiang Zheng, Chao Zhang, Jian Sun
The rapid advancement in point cloud processing technologies has significantly increased the demand for efficient and compact models that achieve high-accuracy classification. Know…
PMT-MAE: Dual-Branch Self-Supervised Learning with Distillation for Efficient Point Cloud Classification
Qiang Zheng, Chao Zhang, Jian Sun
Advances in self-supervised learning are essential for enhancing feature extraction and understanding in point cloud processing. This paper introduces PMT-MAE (Point MLP-Transforme…
PointMT: Efficient Point Cloud Analysis with Hybrid MLP-Transformer Architecture
Qiang Zheng, Chao Zhang, Jian Sun
In recent years, point cloud analysis methods based on the Transformer architecture have made significant progress, particularly in the context of multimedia applications such as 3…
PointViG: A Lightweight GNN-based Model for Efficient Point Cloud Analysis
Qiang Zheng, Yafei Qi, Chen Wang +2
In the domain of point cloud analysis, despite the significant capabilities of Graph Neural Networks (GNNs) in managing complex 3D datasets, existing approaches encounter challenge…