If you force developers to learn Helm, Kustomize, or how Kubernetes manifests work, you are wasting their time. Give them ...

Abstract: Estimating the rigid transformation with 6 degrees of freedom based on a putative 3D correspondence set is a crucial procedure in point cloud registration. Existing correspondence ...

Abstract: The rapid evolution of the Industrial Internet of Things (IIoT) and widespread adoption of smart devices have profoundly reshaped traditional industrial production and management.

Abstract: In this work, we propose a novel segmentation-based explainable artificial intelligence (XAI) method for neural networks working on point cloud classification. As one building block of this ...

Abstract: Point cloud registration (PCR) is an important task for other point cloud tasks. Feature-based methods are widely adopted for their speed and efficiency in PCR. The descriptive capability of ...

Abstract: Mobile computing paradigms have undergone significant transformations with the rise of mobile cloud computing (MCC), mobile edge computing (MEC), and mobile edge cloud computing (MECC).

Abstract: Recently, Point-MAE has extended Masked Autoencoders (MAE) to point clouds for 3D self-supervised learning, which however faces two problems: (1) the shape similarity between the masked ...

Abstract: Point cloud compression significantly reduces data volume but sacrifices reconstruction quality, highlighting the need for advanced quality enhancement techniques. Most existing approaches ...

Abstract: Due to the non-uniform perception of human vision, structural or color changes in salient regions play a dominant role in point cloud quality assessment (PCQA). In this paper, we propose a ...

Abstract: Point cloud upsampling can improve the quality of the initial point cloud, significantly enhancing the performance of downstream tasks such as classification and segmentation. Existing ...

Abstract: Although point cloud segmentation has a principal role in 3D understanding, annotating fully large-scale scenes for this task can be costly and time-consuming. To resolve this issue, we ...

Abstract: Current point cloud registration algorithms struggle to effectively handle both deformations and occlusions simultaneously. Our manifold analysis reveals this limitation arises from the ...