我们在遮蔽器后面看到什么? 复杂对象中的统计属性的amodal完成
1Centre for Neuroscience, Indian Institute of Science, Bengaluru, 560012, India.
Attention, perception & psychophysics
|October 27, 2024
概括
人类的amodal完成是复杂的,外推全球统计特征的封闭形状. 这一过程在简单的形状上似乎是自动的,而不是复杂的形状,与深度网络不同.
科学领域:
- 认知心理学 认知心理学
- 计算神经科学是一种计算神经科学.
- 计算机视觉 计算机视觉 计算机视觉
背景情况:
- 模态完成是对看不见的物体部分的感知推断.
- 目前尚不清楚多复杂的功能是如何模态完成的,以及它是否自动完成.
研究的目的:
- 研究人类的简单和复杂形状的amodal完成.
- 将人类的表现与深层神经网络进行比较.
主要方法:
- 参与者使用隐蔽显示器在分心器中寻找奇怪的目标.
- 显示器具有相同的可见轮,但交换了封闭的部分.
- 分析了全球一致和不一致的完成的搜索时间.
- 对比人类的结果与深度网络预训练对象分类.
主要成果:
- 人类对封闭显示器的搜索时间更好地匹配全球一致的完成,无论是简单的还是复杂的形状.
- 深度网络对简单的形状显示了类似的结果,但并非复杂的形状.
- 深度网络努力推断出复杂的隐蔽轮.
结论:
- 人类的amodal完成是复杂的,利用全球统计属性.
- 对于人类的简单形状,amodal完成似乎是自动的.
- 目前,深度网络缺乏在人类中看到的复杂的amodal完成的复杂性.
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