Person re-identification (Re-ID) technology plays an increasingly crucial role in intelligent
surveillance systems. Widespread occlusion significantly impacts the performance of person …

In recent years, point cloud representation has become one of the research hotspots in the
field of computer vision, and has been widely used in many fields, such as autonomous …

Training deep models for semantic scene completion is challenging due to the sparse and
incomplete input, a large quantity of objects of diverse scales as well as the inherent label …

The task of point cloud segmentation, comprising semantic, instance, and panoptic
segmentation, has been mainly tackled by designing task-specific network architectures …

Chamfer distance (CD) is a standard metric to measure the shape dissimilarity between
point clouds in point cloud completion, as well as a loss function for (deep) learning …

Deep learning (DL) has become one of the mainstream and effective methods for point
cloud analysis tasks such as detection, segmentation and classification. To reduce …

In this paper we explore the recent topic of point cloud completion, guided by an auxiliary
image. We show how it is possible to effectively combine the information from the two …

Scene completion and forecasting are two popular perception problems in research for
mobile agents like autonomous vehicles. Existing approaches treat the two problems in …

Automated shape repair approaches currently lack access to datasets that describe real-
world damaged geometry. We present Fantastic Breaks (and Where to Find Them …

In this paper, we explore a novel framework, EGIInet (Explicitly Guided Information
Interaction Network), a model for View-guided Point cloud Completion (ViPC) task, which …