Brain-inspired algorithms have become a new trend in next-generation artificial intelligence.
Through research on brain science, the intelligence of remote sensing algorithms can be …

Change detection has been increasingly studied in remote and close-range sensing in the
last decades, driven by its importance in environment monitoring and database updating …

Vehicle-to-everything (V2X) communication techniques enable the collaboration between
vehicles and many other entities in the neighboring environment, which could fundamentally …

We describe a simple pre-training approach for point clouds. It works in three steps: 1. Mask
all points occluded in a camera view; 2. Learn an encoder-decoder model to reconstruct the …

As one of the fundamental technologies for scene understanding, semantic segmentation
has been widely explored in the last few years. Light field cameras encode the geometric …

We study the problem of efficient semantic segmentation of large-scale 3D point clouds. By
relying on expensive sampling techniques or computationally heavy pre/post-processing …

We study the problem of 3D semantic segmentation from raw point clouds. Unlike existing
methods which primarily rely on a large amount of human annotations for training neural …

Point cloud analysis (such as 3D segmentation and detection) is a challenging task,
because of not only the irregular geometries of many millions of unordered points, but also …

Labelling point clouds fully is highly time-consuming and costly. As larger point cloud
datasets with billions of points become more common, we ask whether the full annotation is …

Building-change detection underpins many important applications, especially in the military
and crisis-management domains. Recent methods used for change detection have shifted …