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Found 3 papers, 2 papers with code
T-MAE: Temporal Masked Autoencoders for Point Cloud Representation Learning
The scarcity of annotated data in LiDAR point cloud understanding hinders effective representation learning.
APNet: Urban-level Scene Segmentation of Aerial Images and Point Clouds
To leverage the different properties of each branch, we employ a geometry-aware fusion module that is learned to combine the results of each branch.
Personal Fixations-Based Object Segmentation with Object Localization and Boundary Preservation
In this paper, we focus on Personal Fixations-based Object Segmentation (PFOS) to address issues in previous studies, such as the lack of appropriate dataset and the ambiguity in fixations-based interaction.
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