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意义图谱捕捉了场景中局部语义特征的密度：对 Pedziwiatr、Kümmerer、Wallis、Bethge 和 Teufel（2021）的回复。

Meaning maps capture the density of local semantic features in scenes: A reply to Pedziwiatr, Kümmerer, Wallis, Bethge & Teufel (2021).

机构信息

Center for Mind and Brain, University of California, Davis, USA; Department of Psychology, University of California, Davis, USA.

Center for Mind and Brain, University of California, Davis, USA.

出版信息

Cognition. 2021 Sep;214:104742. doi: 10.1016/j.cognition.2021.104742. Epub 2021 Apr 21.

DOI:10.1016/j.cognition.2021.104742
PMID:33892912
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11166323/
Abstract

Pedziwiatr, Kümmerer, Wallis, Bethge, & Teufel (2021) contend that Meaning Maps do not represent the spatial distribution of semantic features in scenes. We argue that Pesziwiatr et al. provide neither logical nor empirical support for that claim, and we conclude that Meaning Maps do what they were designed to do: represent the spatial distribution of meaning in scenes.

摘要

佩齐维亚特、库默勒、瓦利斯、贝斯格和特菲尔（2021 年）认为，语义图并不能代表场景中语义特征的空间分布。我们认为，佩齐维亚特等人既没有提供逻辑支持，也没有提供经验支持来支持这一说法，我们的结论是，语义图完成了它们的设计目的：代表场景中意义的空间分布。

相似文献

1
Meaning maps capture the density of local semantic features in scenes: A reply to Pedziwiatr, Kümmerer, Wallis, Bethge & Teufel (2021).意义图谱捕捉了场景中局部语义特征的密度：对 Pedziwiatr、Kümmerer、Wallis、Bethge 和 Teufel（2021）的回复。
Cognition. 2021 Sep;214:104742. doi: 10.1016/j.cognition.2021.104742. Epub 2021 Apr 21.
2
There is no evidence that meaning maps capture semantic information relevant to gaze guidance: Reply to Henderson, Hayes, Peacock, and Rehrig (2021).没有证据表明语义图可以捕捉到与注视引导相关的语义信息：对 Henderson、Hayes、Peacock 和 Rehrig（2021）的回复。
Cognition. 2021 Sep;214:104741. doi: 10.1016/j.cognition.2021.104741. Epub 2021 Apr 30.
3
Meaning maps detect the removal of local semantic scene content but deep saliency models do not.意义图谱能检测到局部语义场景内容的移除，而深度显著模型则不能。
Atten Percept Psychophys. 2022 Apr;84(3):647-654. doi: 10.3758/s13414-021-02395-x. Epub 2022 Feb 9.
4
Searching for meaning: Local scene semantics guide attention during natural visual search in scenes.寻找意义：局部场景语义在场景自然视觉搜索中引导注意力。
Q J Exp Psychol (Hove). 2023 Mar;76(3):632-648. doi: 10.1177/17470218221101334. Epub 2022 Jun 8.
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Meaning guides attention during scene viewing, even when it is irrelevant.意义在场景观看过程中引导注意力，即使它并不相关。
Atten Percept Psychophys. 2019 Jan;81(1):20-34. doi: 10.3758/s13414-018-1607-7.
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The role of meaning in attentional guidance during free viewing of real-world scenes.意义在自由观看真实世界场景时的注意力引导中的作用。
Acta Psychol (Amst). 2019 Jul;198:102889. doi: 10.1016/j.actpsy.2019.102889. Epub 2019 Jul 11.
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The role of local meaning in infants' fixations of natural scenes.当地意义在婴儿对自然场景的注视中的作用。
Infancy. 2024 Mar-Apr;29(2):284-298. doi: 10.1111/infa.12582. Epub 2024 Jan 6.
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Meaning guides attention in real-world scene images: Evidence from eye movements and meaning maps.意义在真实场景图像中引导注意力：来自眼动和意义地图的证据。
J Vis. 2018 Jun 1;18(6):10. doi: 10.1167/18.6.10.
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Meaning and expected surfaces combine to guide attention during visual search in scenes.意义和预期表面结合起来指导场景中视觉搜索时的注意力。
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Meaning Guides Attention during Real-World Scene Description.意义引导在现实场景描述中的注意力。
Sci Rep. 2018 Sep 10;8(1):13504. doi: 10.1038/s41598-018-31894-5.

引用本文的文献

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Saliency models perform best for women's and young adults' fixations.显著性模型在预测女性和年轻人的注视点方面表现最佳。
Commun Psychol. 2023 Nov 17;1(1):34. doi: 10.1038/s44271-023-00035-8.
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Look at what I can do: Object affordances guide visual attention while speakers describe potential actions.看看我能做什么：当说话者描述潜在动作时，物体可供性引导视觉注意。
Atten Percept Psychophys. 2022 Jul;84(5):1583-1610. doi: 10.3758/s13414-022-02467-6. Epub 2022 Apr 28.
3
Semantic object-scene inconsistencies affect eye movements, but not in the way predicted by contextualized meaning maps.语义物体-场景不一致会影响眼球运动，但与语境化意义图谱预测的方式不同。
J Vis. 2022 Feb 1;22(2):9. doi: 10.1167/jov.22.2.9.
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Meaning maps detect the removal of local semantic scene content but deep saliency models do not.意义图谱能检测到局部语义场景内容的移除，而深度显著模型则不能。
Atten Percept Psychophys. 2022 Apr;84(3):647-654. doi: 10.3758/s13414-021-02395-x. Epub 2022 Feb 9.
5
Deep saliency models learn low-, mid-, and high-level features to predict scene attention.深度显著模型学习低、中、高级特征来预测场景注意力。
Sci Rep. 2021 Sep 16;11(1):18434. doi: 10.1038/s41598-021-97879-z.
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Disrupted object-scene semantics boost scene recall but diminish object recall in drawings from memory.记忆中绘画的客体-场景语义关系破坏会增强场景回忆，但削弱客体回忆。
Mem Cognit. 2021 Nov;49(8):1568-1582. doi: 10.3758/s13421-021-01180-3. Epub 2021 May 24.

本文引用的文献

1
Looking for Semantic Similarity: What a Vector-Space Model of Semantics Can Tell Us About Attention in Real-World Scenes.寻找语义相似性：语义向量空间模型可以告诉我们关于现实场景中注意力的什么信息。
Psychol Sci. 2021 Aug;32(8):1262-1270. doi: 10.1177/0956797621994768. Epub 2021 Jul 12.
2
Progress Toward Resolving the Attentional Capture Debate.解决注意力捕获争论的进展。
Vis cogn. 2021;29(1):1-21. doi: 10.1080/13506285.2020.1848949. Epub 2020 Dec 1.
3
Meaning maps and saliency models based on deep convolutional neural networks are insensitive to image meaning when predicting human fixations.基于深度卷积神经网络的意义图和显著度模型在预测人类注视时对图像意义不敏感。
Cognition. 2021 Jan;206:104465. doi: 10.1016/j.cognition.2020.104465. Epub 2020 Oct 20.
4
Where the eyes wander: The relationship between mind wandering and fixation allocation to visually salient and semantically informative static scene content.目光游移之处：心流游移与视觉显著和语义信息丰富的静态场景内容的注视分配之间的关系。
J Vis. 2020 Sep 2;20(9):10. doi: 10.1167/jov.20.9.10.
5
Active vision in immersive, 360° real-world environments.沉浸式 360° 真实环境中的主动视觉。
Sci Rep. 2020 Aug 31;10(1):14304. doi: 10.1038/s41598-020-71125-4.
6
Neural Correlates of Fixated Low- and High-level Scene Properties during Active Scene Viewing.主动观看场景时注视的低水平和高水平场景属性的神经相关物。
J Cogn Neurosci. 2020 Oct;32(10):2013-2023. doi: 10.1162/jocn_a_01599. Epub 2020 Jun 23.
7
Why do we retrace our visual steps? Semantic and episodic memory in gaze reinstatement.为什么我们会重走视觉路径？眼动恢复中的语义和情节记忆。
Learn Mem. 2020 Jun 15;27(7):275-283. doi: 10.1101/lm.051227.119. Print 2020 Jul.
8
Where the action could be: Speakers look at graspable objects and meaningful scene regions when describing potential actions.行为可能发生的地方：说话者在描述潜在动作时会看可抓取的物体和有意义的场景区域。
J Exp Psychol Learn Mem Cogn. 2020 Sep;46(9):1659-1681. doi: 10.1037/xlm0000837. Epub 2020 Apr 9.
9
The Changing Landscape: High-Level Influences on Eye Movement Guidance in Scenes.不断变化的格局：场景中对眼动引导的高级影响。
Vision (Basel). 2019 Jun 28;3(3):33. doi: 10.3390/vision3030033.
10
Meaning and Attentional Guidance in Scenes: A Review of the Meaning Map Approach.场景中的意义与注意力引导：意义地图方法综述
Vision (Basel). 2019 May 10;3(2):19. doi: 10.3390/vision3020019.