3D object detection, of which the goal is to obtain the 3D spatial structure information of the object, is a challenging topic in many visual perception systems, e.g., autonomous driving, augmented reality, and
Multi-modal object detectionVision-language modelsFrequency moduleMulti-modal 3D object detection methods combine data from multiple sensors, like cameras and LiDAR, to improve environmental perception. However, these methods are confined to learning representations within a closed vocabulary context and ...
近年来常用且成熟的2D检测方法可以在3D检测中复用。 2.2.1 单目3D目标检测(Monocular 3D Object Detection) 单目相机以像素强度的形式提供密集信息,揭示形状和纹理属性。形状和纹理信息也可以用来检测车道几何,交通标志和对象的类型。使用单目相机进行三维探测的主要缺点是缺乏深度信息,而深度信息是AVs准确估计目标尺寸和位...
Multi-modal 3D object detection has achieved remarkable progress, but it is often limited in practical industrial production because of its high cost and low efficiency. The multi-view camera-based method provides a feasible solution due to its low cost. However, camera data lacks geometric depth...
UniBEV: Multi-modal 3D Object Detection with Uniform BEV Encoders bacon 中国科学院大学 模式识别与智能系统博士 4 人赞同了该文章 关键字 多传感器融合、多模态、BEV、3D Detection 摘要 研究目标:提出一种多模态3D物体检测模型,能够在一个或多个传感器输入缺失的情况下,保持鲁棒性和准确性。
To tackle the problem, we propose a novel multi-modal object detection model that is built upon a hierarchical transformer and cross-guidance between different modalities. The proposed hierarchical transformer consists of domain-specific feature extraction networks where intermediate features are connected ...
摘要: 点云和RGB是两个主要的数据形式在3d目标检测领域。燃油由于模态的较大差异性,很难有效的使用。为了解决这个问题:提出了一个新颖的框架,命名为Contrastively Augmented Transformer formulti-modal3D object Detection (CAT-Det) 相对增广的Transformer用于多模态3d目标检测。CAT 构建了一个双通道结构网络,一个结构...
多模态融合: DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection，这研究探讨了如何在自动驾驶领域中，通过整合激光雷达和相机数据进行三维物体检测，以提高检测精度和可靠性。面对现有技术的局限性，研究团队提出了一种创新的深度特征融合策略，旨在解决传统方法中出现的挑战，包括特征...
Noise has always been nonnegligible trouble in object detection by creating confusion in model reasoning, thereby reducing the informativeness of the data. It can lead to inaccurate recognition due to the shift in the observed pattern, that requires a robust generalization of the models. To implement...
FIG. 6 illustrates an example of an object detection framework; FIG. 7 illustrates a flow diagram of example logic for an object detection framework; FIG. 8 illustrates an example of an object classification controller; FIG. 9 illustrates a flow diagram of example logic for an object classificat...