GitHub

ZiyuGuo99/Point-Bind_Point-LLM

Official implementation of 'Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following'. Using Point-Bind, we introduce Point-LLM, the ...
IEEE

Learning-Based Sampling Method for Point Cloud Segmentation

Abstract: Light detection and ranging (LiDAR) has become one of the most important sensors in 3-D perception. With the advancement of sensor technology, the point cloud data generated by LiDAR have ...
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

Learning-Based Reflection-Aware Virtual Point Removal for Large-Scale 3D Point Clouds

Abstract: 3D point clouds are widely used for robot perception and navigation. LiDAR sensors can provide large scale 3D point clouds (LS3DPC) with a certain level of accuracy in common environment.
TechAnnouncer

Master Java Coding: Top Free Online Practice Resources for 2026

While the basic course is free and great for getting started, they also have a ‘Pro’ version if you want to dig deeper. It’s a solid choice if you’re totally new to programming and want a smooth, ...
IEEE

Class Incremental Learning With Less Forgetting Direction and Equilibrium Point

Abstract: Catastrophic forgetting is the core problem of class incremental learning (CIL). Existing work mainly adopts memory replay, knowledge distillation, and dynamic architecture to alleviate this ...
IEEE

PCDNF: Revisiting Learning-Based Point Cloud Denoising via Joint Normal Filtering

Abstract: Point cloud denoising is a fundamental and challenging problem in geometry processing. Existing methods typically involve direct denoising of noisy input or filtering raw normals followed by ...
IEEE

Transitioning From Federated Learning to Quantum Federated Learning in Internet of Things: A Comprehensive Survey

Abstract: Quantum Federated Learning (QFL) recently becomes a promising approach with the potential to revolutionize Machine Learning (ML). It merges the established strengths of classical Federated ...
IEEE

Deep Learning-Based Point Cloud Compression: An In-Depth Survey and Benchmark

Abstract: With the maturity of 3D capture technology, the explosive growth of point cloud data has burdened the storage and transmission process. Traditional hybrid point cloud compression (PCC) tools ...
IEEE

PointWavelet: Learning in Spectral Domain for 3-D Point Cloud Analysis

Abstract: With recent success of deep learning in 2-D visual recognition, deep-learning-based 3-D point cloud analysis has received increasing attention from the community, especially due to the rapid ...
IEEE

SphereNet: Learning a Noise-Robust and General Descriptor for Point Cloud Registration

Abstract: Point cloud registration aims to estimate a transformation that aligns point clouds collected from different perspectives. In learning-based point cloud registration, a robust descriptor is ...
IEEE

A Sequential and Asynchronous Federated Learning Framework for Railway Point Machine Fault Diagnosis With Imperfect Data Transmission

Abstract: Fault diagnosis of railway assets has drawn the interest of both the scholarly and engineering communities. Federated learning (FL) enables training models across distributed assets to ...