IEEE

Applying Machine Learning on Big Data With Apache Spark

Abstract: The exponential growth of data in the digital age has necessitated the development of frameworks capable of efficiently handling and processing vast datasets. This paper explores the ...
IEEE

Deep Scene Flow Learning: From 2D Images to 3D Point Clouds

Abstract: Scene flow describes the 3D motion in a scene. It can be modeled as a single task or as a composite of the auxiliary tasks of depth, camera motion, and optical flow estimation. Deep learning ...
IEEE

An Improved Sequence-to-Point Learning for Non-Intrusive Load Monitoring Based on Discrete Wavelet Transform

Abstract: Nonintrusive load monitoring (NILM) is a process that monitors the aggregated power consumption data of customers measured by a single sensor and decomposes the real-time power consumption ...
GitHub

GeoFormer: Learning Point Cloud Completion with Tri-Plane Integrated Transformer

In this paper, we introduce a GeoFormer that simultaneously enhances the global geometric structure of the points and improves the local details. Specifically, we design a CCM Feature Enhanced Point ...
IEEE

Toward Visual Interaction: Hand Segmentation by Combining 3-D Graph Deep Learning and Laser Point Cloud for Intelligent Rehabilitation

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 ...
IEEE

Deep Learning-Based Pedestrian Detection Using RGB Images and Sparse LiDAR Point Clouds

Abstract: One of the fundamental tasks in autonomous driving is environment perception for pedestrian detection, where the fused pedestrian detection using camera and light detection and ranging ...
IEEE

A Novel Point Cloud Deep Learning Method for Predicting Variable Airfoil Flow Fields

Abstract: Airfoil flow field is of great significance to the design optimization of aircraft shape. Convolutional Neural Networks (CNNs) have been applied in flow field prediction studies, which ...
IEEE

A Simple Framework of Few-Shot Learning Using Sparse Annotations for Semantic Segmentation of 3-D Point Clouds

Abstract: The semantic segmentation of point clouds plays a crucial role in the interpretation of 3-D scene. However, the majority of supervised learning methods needs a great number of annotated data ...
IEEE

LLM-Guided Cross-Modal Point Cloud Quality Assessment: A Graph Learning Approach

Abstract: This paper addresses the critical need for accurate and reliable point cloud quality assessment (PCQA) in various applications, such as autonomous driving, robotics, virtual reality, and 3D ...
IEEE

Matching Distance and Geometric Distribution Aided Learning Multiview Point Cloud Registration

Abstract: Multiview point cloud registration plays a crucial role in robotics, automation, and computer vision fields. This letter concentrates on pose graph construction and motion synchronization ...
IEEE

PointOBB: Learning Oriented Object Detection via Single Point Supervision

Abstract: Single point-supervised object detection is gaining attention due to its cost-effectiveness. However, existing approaches focus on generating horizontal bounding boxes (HBBs) while ignoring ...
IEEE

GraphI2P: Image-to-Point Cloud Registration with Exploring Pattern of Correspondence via Graph Learning

Abstract: Although the fusion of images and LiDAR point clouds is crucial to many applications in computer vision, the relative poses of cameras and LiDAR scanners are often unknown. However, due to ...