ALICE-LRI (Automatic LiDAR Intrinsic Calibration Estimation for Lossless Range Images) is a C++ and Python library for lossless range image generation and reconstruction from spinning 3D LiDAR point ...

Introduction: Accurate 3D reconstruction is essential for plant phenotyping. However, point clouds generated directly by binocular cameras using single-shot mode often suffer from distortion, while ...

UniPre3D is the first unified pre-training method for 3D point clouds that effectively handles both object- and scene-level data through cross-modal Gaussian splatting. Our proposed pre-training task ...

Google Cloud has announced the launch of GCUL (Google Cloud Universal Ledger), a Layer-1 blockchain designed specifically for financial institutions and enterprises. The move signals Google’s most ...

Abstract: With recent developments of convolutional neural net-works, deep learning for 3D point clouds has shown significant progress in various 3D scene understanding tasks, e.g., object recognition ...

3D self-supervised learning (SSL) has faced persistent challenges in developing semantically meaningful point representations suitable for diverse applications with minimal supervision. Despite ...

Point cloud-based 3D object detection is a key technology in autonomous driving and mobile robot perception systems. However, the sparsity and irregularity of point cloud data result in poor ...

Three-dimensional (3D) LiDAR is crucial for the autonomous navigation of orchard mobile robots, offering comprehensive and accurate environmental perception. However, the increased richness of ...