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Image attention transformer network for indoor 3D object detection
Point clouds and RGB images are both critical data for 3D object detection. While recent multi-modal methods combine them directly and show...
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3D Object Detection
This chapter provides an overview of 3D object detection methods, starting with an introduction to sensors and datasets commonly used in autonomous...
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Detection-driven 3D masking for efficient object gras**
Robotic arms are currently in the spotlight of the industry of future, but their efficiency faces huge challenges. The efficient gras** of the...
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MMFG: Multimodal-based Mutual Feature Gating 3D Object Detection
To address the problem that image and point cloud features are fused in a coarse fusion way and cannot achieve deep fusion, this paper proposes a...
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Impact of LiDAR point cloud compression on 3D object detection evaluated on the KITTI dataset
The rapid growth on the amount of generated 3D data, particularly in the form of Light Detection And Ranging (LiDAR) point clouds (PCs), poses very...
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MonoSAID: Monocular 3D Object Detection based on Scene-Level Adaptive Instance Depth Estimation
Monocular 3D object detection (Mono3OD) is a challenging yet cost-effective vision task in the fields of autonomous driving and mobile robotics. The...
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Adaptive learning point cloud and image diversity feature fusion network for 3D object detection
3D object detection is a critical task in the fields of virtual reality and autonomous driving. Given that each sensor has its own strengths and...
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3D Object Detection for Autonomous Driving
As an important application of Artificial Intelligence (AI), autonomous driving has developed rapidly in recent years. 3D object detection in...
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Robust Environmental Perception of Monocular 3D Object Detection
The main role of monocular vision based 3D object detection in intelligent vehicles is to extract obstacle information from the environment,...
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Overview of 3D Object Detection for Robot Environment Perception
Environmental perception is one of the key issues in robot research. To complete more precise tasks, robots need a recognition ability to recognize...
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Towards Real-Time 3D Object Detection Through Inverse Perspective Map**
3D object detection in road scenes is crucial for computer vision applications. While traditional 2D object detection has seen remarkable success, 3D...
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Occlusion Problem in 3D Object Detection: A Review
In computer vision, 3D object detection has numerous applications such as robotics, augmented reality (AR), medical field, manufacturing industries,...
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DCGNN: a single-stage 3D object detection network based on density clustering and graph neural network
Currently, single-stage point-based 3D object detection network remains underexplored. Many approaches worked on point cloud space without...
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3D Object Detection in Point Cloud Using Key Point Detection Network
This paper improves an existing model which is used in real time to detect an object in the 3D point cloud. We have used ResNet-based Key point...
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Few-Shot Online Learning for 3D Object Detection in Autonomous Driving
For autonomous driving, the performance of 3D object detection is limited by offline training, and these methods usually lack the adaption ability...
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RGB Image- and Lidar-Based 3D Object Detection Under Multiple Lighting Scenarios
In recent years, camera- and lidar-based 3D object detection has achieved great progress. However, the related researches mainly focus on normal...
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Evaluation of Point Cloud Data Augmentation for 3D-LiDAR Object Detection in Autonomous Driving
Obstacle detection is an essential component for autonomous vehicles to navigate safely. To address certain limitations of 2D object detection,...
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A Systematic Review on LiDAR-Based 3D Object Detection
Light Detection And Ranging (LiDAR) is a popular sensor for providing 3-Dimensional (3D) information about a point cloud to localize and characterize...
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Voxel R-CNN-MCA: Coordinate Attention for 3D Object Detection
With the development of autonomous driving technology, autonomous vehicles have gradually moved from ideal highways to more realistic urban...
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CNN-Based Object Detection and Distance Prediction for Autonomous Driving Using Stereo Images
Convolutional neural networks (CNNs) have been successful for tasks such as object detection; however, they involve time-consuming processes....