Vladimir Zakharov explains how DataFrames serve as a vital tool for data-oriented programming in the Java ecosystem. By ...
Abstract: Existing methods for learning 3D point cloud representation often use a single dataset-specific training and testing approach, leading to performance drops due to significant domain shifts ...
Abstract: Rapid and accurate segmentation of 3D point clouds is critical for optimizing battery-swapping robots and ensuring precise assembly. To address the challenges of computational inefficiency ...
Abstract: Point cloud quality assessment (PCQA) is a challenging task due to the inherently disordered nature of points. Existing point-based methods, such as sparse convolution and PointNet, are ...
Abstract: Due to the irregular and disordered data structure in 3D point clouds, prior works have focused on designing more sophisticated local representation methods to capture these complex local ...
Abstract: Effective sampling plays a critical role in the preprocessing of 3D point cloud data, directly impacting the performance of downstream models. Traditional Farthest Point Sampling (FPS) ...
Traditional models struggle to explain why mobile hunter-gatherers would invest so heavily in permanent architecture and long-distance exchange. poverty-point-signaling/ ├── src/poverty_point/ # ...