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Found 4 papers, 0 papers with code
Refining Segmentation On-the-Fly: An Interactive Framework for Point Cloud Semantic Segmentation
This paper concentrates on an unexplored yet meaningful task, i. e., interactive point cloud semantic segmentation, which assigns high-quality semantic labels to all points in a scene with user corrective clicks.
Joint Data and Feature Augmentation for Self-Supervised Representation Learning on Point Clouds
To address the issues, we propose a simple but efficient augmentation fusion contrastive learning framework to combine data augmentations in Euclidean space and feature augmentations in feature space.
Hypergraph Convolutional Network based Weakly Supervised Point Cloud Semantic Segmentation with Scene-Level Annotations
Secondly, the WHCN takes the hypergraph as input and learns to predict high-precision point-level pseudo labels by label propagation.
AS-PD: An Arbitrary-Size Downsampling Framework for Point Clouds
Given an input point cloud of arbitrary size, we first perform a task-agnostic pre-sampling on the input point cloud to a specified sample size.
