Lidar

LiDM: The First Method to Generate Realistic Lidar Scenes Based on Multimodal Conditions

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LiDM: The First Method to Generate Realistic Lidar Scenes Based on Multimodal Conditions

Follow our WeChat public account to discover the beauty of CV technology This article shares the CVPR 2024 paper LiDAR Diffusion: Towards Realistic Scene Generation with LiDAR Diffusion Models, which utilizes LiDAR diffusion models to generate realistic scenes. Details are as follows: Paper link: https://arxiv.org/abs/2404.00815 Code link: https://github.com/hancyran/LiDAR-Diffusion Project homepage: https://lidar-diffusion.github.io/ Background In recent years, … Read more

A Comprehensive Review of Multi-Modal Fusion Perception in Autonomous Driving

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A Comprehensive Review of Multi-Modal Fusion Perception in Autonomous Driving

Introduction Multi-modal fusion is a crucial task in the perception of autonomous driving systems. This article will detail the multi-modal perception methods for autonomous driving, including object detection and semantic segmentation tasks involving LiDAR and cameras. From the perspective of the fusion stage, existing solutions are categorized into data-level, feature-level, object-level, and asymmetric fusion. Furthermore, … Read more

Latest Review on Multi-Modal 3D Object Detection in Autonomous Driving

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Latest Review on Multi-Modal 3D Object Detection in Autonomous Driving

Source｜Public Account: Heart of Autonomous Driving Autonomous vehicles require continuous environmental perception to understand the distribution of obstacles for safe driving. Specifically, 3D object detection is a crucial functional module as it can predict the category, location, and size of surrounding objects simultaneously. Generally, autonomous cars are equipped with multiple sensors, including cameras and LiDAR. … Read more

2022 Latest Review: Detailed Explanation of Multi-Modal Fusion Perception Algorithms in Autonomous Driving

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2022 Latest Review: Detailed Explanation of Multi-Modal Fusion Perception Algorithms in Autonomous Driving

About 4300 words, recommended reading time 5 minutes. This article classifies the field into two major categories and four subcategories based on the fusion stage, and also analyzes the existing problems in the current field, providing references for future research directions. 1 Introduction Multi-modal sensor fusion means complementary, stable, and safe information, and has long … Read more

Summary of Multimodal 3D Object Detection Development Methods

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Summary of Multimodal 3D Object Detection Development Methods

Source丨Heart of Autonomous Driving Editor丨Deep Blue Academy What is Multimodal 3D Object Detection? Multimodal 3D object detection is one of the current research hotspots in 3D object detection, mainly referring to the use of cross-modal data to improve the detection accuracy of the model. Generally speaking, multimodal data includes: image data, LiDAR data, millimeter-wave radar … Read more

Overview of 50+ Multimodal Image Fusion Methods

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Overview of 50+ Multimodal Image Fusion Methods

MLNLP(Machine Learning Algorithms and Natural Language Processing) community is a well-known natural language processing community at home and abroad, covering NLP master’s and doctoral students, university teachers, and corporate researchers. The Vision of the Communityis to promote communication and progress between the academic and industrial circles of natural language processing and machine learning at home … Read more

Defects of Huawei’s ADS Lidar Solution From Attention Mechanism

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Defects of Huawei's ADS Lidar Solution From Attention Mechanism

This article assumes you are familiar with the Transformer Attention mechanism. If not, that’s okay; let me explain briefly. The Attention mechanism refers to the focus point; the same event can have different focal points for different people. For instance, the teacher says: “Xiao Ming skipped class again to play basketball.” The teacher’s focus is … Read more