Abstract: Place recognition is a fundamental component of robotics, and has seen tremendous improvements through the use of deep learning models in recent years. Networks can experience significant ...
Abstract: Against the backdrop of the increasing trend of aging population in China and even globally, the demand for hand function rehabilitation is growing day by day, and human-machine interaction ...
Abstract: Point cloud completion is to restore complete 3D scenes and objects from incomplete observations or limited sensor data. Existing fully-supervised methods rely on paired datasets of ...
Abstract: Deep learning techniques have been evolving at a faster pace offering a common framework for developing models for various applications using remote sensing data. Availability of high ...
Abstract: To address the drawbacks that current multibeam bathymetric outlier removal methods lack repeatability, often require parameter adjustment for different regions, still require a lot of ...
Abstract: In this study, deep learning techniques and algorithms used in point cloud processing have been analysed. Methods, technical properties and algorithms developed for 3D Object Classification ...
Abstract: Point cloud filtering and normal estimation are two fundamental research problems in the 3D field. Existing methods usually perform normal estimation and filtering separately and often show ...
Abstract: Point scene instance mesh reconstruction is a challenging task since it requires both scene-level instance segmentation and instance-level mesh reconstruction from partial observations ...
Abstract: Optimal access point (AP) placement inside an industrial layout is important to ensure excellent connectivity. However, wireless fidelity (Wi-Fi) AP placement is complicated because ...
Abstract: Since point clouds acquired by scanners inevitably contain noise, recovering a clean version from a noisy point cloud is essential for further 3D geometry processing applications. Several ...
Abstract: Point cloud semantic segmentation has achieved considerable progress in the past decade. To alleviate expensive data annotation efforts, weakly supervised learning methods are preferable, ...
Abstract: Self-supervised learning has achieved significant success in various fields such as point cloud detection and segmentation. However, self-supervised learning for point cloud registration is ...
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