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相关概念视频

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
Visual System01:26

Visual System

Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
Multiple Pipe Systems01:21

Multiple Pipe Systems

Multipipe systems consist of complex configurations of interconnected pipes designed to transport fluids efficiently across intricate networks. They are essential in engineering applications requiring precise control over flow distribution, pressure, and head loss. They are categorized into series, parallel, loop, and network configurations, each distinguished by unique flow characteristics and applications.
Series Configuration
In a series configuration, fluid flows sequentially from one pipe...

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相关实验视频

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Cross-Modal Multivariate Pattern Analysis
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BSI-MVS:具有双向语义信息的多视图立体网络.

Ruiming Jia1, Jun Yu1, Zhenghui Hu2

  • 1School of Information Science and Technology, North China University of Technology, Beijing, 100144, China.

Scientific reports
|March 22, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种双向语义信息 (BSI-MVS) 网络,用于高效的3D重建. BSI-MVS显著提高了深度图的准确性,同时减少了多视图立体机任务中的计算复杂性.

关键词:
3D重建重建的3D重建这是双向LSTM.多视图立体声变压器变压器变压器

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科学领域:

  • 计算机视觉 计算机视觉
  • 3D重建的3D重建
  • 机器学习 机器学习

背景情况:

  • 多视图立体声 (MVS) 从多个图像中重建3D场景.
  • 当前最先进的MVS网络通常依赖视觉变压器,导致高计算成本.
  • 提高MVS的效率和准确性对于实际应用至关重要.

研究的目的:

  • 开发一种新的MVS网络,以减少计算复杂性.
  • 为了提高MVS中深度地图生成的准确性.
  • 引入一种有效捕获语义信息用于3D重建的方法.

主要方法:

  • 提出了一个双向语义信息 (BSI-MVS) 网络.
  • 设计了一个多层空间金字塔模块,用于多规模的特征提取.
  • 实现了一个2D双向-LSTM模块来捕获语义上下文.
  • 利用了基于多层次功能构建的成本量,用于深度地图优化.

主要成果:

  • 与现有方法相比,BSI-MVS网络表现出优越的性能.
  • 与TransMVSNet (17.84%),CasMVSNet (36.42%),CVP-MVSNet (14.96%) 和AACVP-MVSNet (4.86%) 相比,取得了显著的改进.
  • 在重建的深度地图的客观指标和视觉质量方面展示了明显的改进.

结论:

  • BSI-MVS网络有效地减少了MVS中的计算复杂性.
  • 拟议的方法显著提高了深度地图的准确性.
  • BSI-MVS为高效准确的3D重建提供了一个有前途的方法.