LU-mamba:通过在远程图像上的双向状态空间建模进行LiDAR上样
概括
通过使用一种新型状态空间模型 (SSM) 方法,LU-Mamba 增强了 LiDAR 的升级采样. 这种方法从稀疏的输入中重建密集的3D点云,优于自主系统的现有技术.
科学领域:
- 计算机视觉 计算机视觉
- 机器人技术 机器人技术 机器人技术
- 机器学习 机器学习
背景情况:
- 从稀疏的输入中生成高分辨率的3D点云,对自动驾驶和机器人感知至关重要.
- 目前的方法通常将3D LiDAR数据转换为2D范围图像,并使用卷积或变压器架构进行超分辨率.
- 将国家空间模型 (SSM) 等先进的序列模型适应到 LiDAR 上采样中,是一个有前途的研究途径.
研究的目的:
- 介绍LU-Mamba,这是一个使用Mamba架构进行LiDAR升级采样的新框架.
- 将Mamba模型专门针对LiDAR范围图像的定向特征进行定制,重点关注垂直轴上采样.
- 从稀疏的LiDAR数据重建密集点云的精度和效率提高.
主要方法:
- 开发了基于Mamba的框架LU-Mamba,这是一个高效的状态空间模型 (SSM) 用于长序列建模.
- 引入了双向Mamba组,通过扫描图像行以上向下和下向上来捕捉远程垂直依赖.
- 整合了具有方向调制的方向感知Mamba模块,以提高对扫描方向和自适应融合的灵敏度.
主要成果:
- LU-Mamba 在基准LiDAR上采样数据集上取得了最先进的性能.
- 提出的方法在点云重建质量方面超过了现有的卷积和基于变压器的方法.
- 废弃性研究证实了双向马巴组和方向感知马巴模块的有效性.
结论:
- 通过利用Mamba的序列建模功能,LU-Mamba代表了LiDAR采样中的重大进步.
- 定向适应是有效处理LiDAR范围图像以改善感知任务的关键.
- 该框架为自动驾驶系统中高分辨率3D点云生成提供了一个新的,高性能替代方案.
相关概念视频
Upsampling
565
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
565
State Space Representation
496
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
Consider an RLC circuit, a...
496
Bandpass Sampling
456
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
456
State Space to Transfer Function
533
The conversion of state-space representation to a transfer function is a fundamental process in system analysis. It provides a method for transitioning from a time-domain description to a frequency-domain representation, which is crucial for simplifying the analysis and design of control systems.
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
533


