Search Results for author:
Found 4 papers, 2 papers with code
Enhanced Prototypical Learning for Unsupervised Domain Adaptation in LiDAR Semantic Segmentation
We evaluate the performance of our method on the recently proposed LiDAR segmentation UDA scenarios.
Projection-based Point Convolution for Efficient Point Cloud Segmentation
Point branch consists of MLPs, while projection branch transforms point features into a 2D feature map and then apply 2D convolutions.
An empirical study of a pruning mechanism
For the pruning and retraining phase, whether the pruned-and-retrained network benefits from the pretrained network indded is examined.
PBP-Net: Point Projection and Back-Projection Network for 3D Point Cloud Segmentation
In this paper, we propose a simple and efficient architecture named point projection and back-projection network (PBP-Net), which leverages 2D CNNs for the 3D point cloud segmentation.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
