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相关概念视频

Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

501
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.
501
Vision01:24

Vision

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Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
52.8K
Visual System01:26

Visual System

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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...
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相关实验视频

Updated: May 22, 2025

Development of an Audio-based Virtual Gaming Environment to Assist with Navigation Skills in the Blind
09:01

Development of an Audio-based Virtual Gaming Environment to Assist with Navigation Skills in the Blind

Published on: March 27, 2013

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PanoGen++:为视觉和语言导航创建域调整的文本引导的全景环境.

Sen Wang1, Dongliang Zhou2, Liang Xie3

  • 1College of Intelligence and Computing, Tianjin University, Tianjin, 300354, China; Tianjin Artificial Intelligence Innovation Center, Tianjin, 300450, China.

Neural networks : the official journal of the International Neural Network Society
|March 13, 2025
PubMed
概括

PanoGen++为视觉和语言导航 (VLN) 任务生成多样化的全景环境,克服数据稀缺. 该框架可以在复杂的导航场景中提高代理性能和概括性.

关键词:
跨模式的学习学习.多媒体计算多媒体计算文本到图像的生成.视觉和语言导航导航

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A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
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A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

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相关实验视频

Last Updated: May 22, 2025

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A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
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科学领域:

  • 人工智能的人工智能
  • 机器人技术 机器人技术 机器人技术
  • 计算机视觉 计算机视觉

背景情况:

  • 视觉语言导航 (VLN) 代理需要广泛的训练数据来使用自然语言在3D环境中导航.
  • 数据稀缺是一个重要的瓶,阻碍了VLN研究的进步和泛化.

研究的目的:

  • 引入PanoGen++,这是一个创新的框架,用于为VLN任务生成多样化和相关的全景培训环境.
  • 通过创建合成但相关的环境来解决VLN中有限的培训数据的挑战.

主要方法:

  • 使用预先训练的扩散模型,具有特定域微调和参数高效的低级调整.
  • 研究了用于创建新型环境的蒙面图像 inpainting 和用于空间关系学习的递归图像 outpainting.

主要成果:

  • 在房间对房间 (R2R) 排行榜上取得了2.44%的成功率增长.
  • 在房间对房间 (R4R) 验证未见集上,性能提高了0.63%.
  • 在合作视觉和对话导航 (CVDN) 验证未见集中,提高了0.75米的目标进展.

结论:

  • PanoGen++有效地增加了培训数据的多样性和对VLN的相关性.
  • 该框架带来了导航代理的更好的通用化和有效性.
  • 在多个基准VLN数据集中展示了显著的性能增长.