Abstract: Point cloud is a popular and widely used geometric representation, which has attracted significant attention in 3D vision. However, the geometric variability of point cloud representations ...
Abstract: In the past decade, deep neural networks have achieved significant progress in point cloud learning. However, collecting large-scale precisely-annotated point clouds is extremely laborious ...
Abstract: Traditional passive point cloud acquisition systems, such as lidars or stereo cameras, can be impractical in real-life and industrial use cases. Firstly, some extreme environments may ...
Abstract: The proposed research develops a unique solar power Maximum Power Point Tracking (MPPT) system which implements Deep Learning approaches within a connected grid power system. Artificial ...
Abstract: Recent advancements in self-supervised learning in the point cloud domain have demonstrated significant potential. However, these methods often suffer from drawbacks such as lengthy ...
Abstract: Point cloud registration aligns 3D point clouds using spatial transformations. It is an important task in computer vision, with applications in areas such as augmented reality (AR) and ...
Abstract: Masked autoencoding has gained momentum for improving fine-tuning performance in many downstream tasks. However, it tends to focus on low-level reconstruction details, lacking high-level ...
Zero-shot language-guided UAV control. See, Point, Fly (SPF) enables UAVs to navigate to any goal based on free-form natural language instructions in any environment, without task-specific training.
Abstract: Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks continue to pose significant threats to networked systems, causing disruptions that can lead to substantial financial ...
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