Few-shot semantic segmentation (FSS) is a challenging task that aims to learn to segment
novel categories with only a few labeled images, and it has a wide range of real-world …

Recently, self-attention networks achieve impressive performance in point cloud
segmentation due to their superiority in modeling long-range dependencies. However …

Learning per-point semantic features from the hierarchical feature pyramid is essential for
point cloud semantic segmentation. However, most previous methods suffered from …

In this paper, we propose a novel joint instance and semantic segmentation approach,
called JSNet++, to address the instance and semantic segmentation tasks of 3D point clouds …

This paper revisits few-shot 3D point cloud semantic segmentation (FS-PCS) with a focus on
two significant issues in the state-of-the-art: foreground leakage and sparse point …

We investigate the problem of 3D point clouds semantic segmentation. Recently, a large
amount of research work has focused on local feature aggregation. However, the …

Video question answering (VideoQA) is a challenging video understanding task that
requires a comprehensive understanding of multimodal information and accurate answers to …

Urban management and survey departments have begun investigating the feasibility of
acquiring data from various laser scanning systems for urban infrastructure measurements …

Most modern approaches in temporal action localization (TAL) mainly focus on time domain
information, while neglecting the advantages of information from other domains. How to …

Mobile LiDAR technology is a powerful tool that accurately captures spatial information
about typical static objects in road scenes. However, the precise extraction and classification …