The importance of shape in early lexical learning
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Object shape is the single most important cue for human object recognition, much more than other cues like size or texture.
“it is well-known that object shape is the single most important cue for human object recognition (Landau et al., 1988), much more than other cues like size or texture”
From ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness (2018) · cites this paper as Landau et al., 1988
Cites
Basic objects in natural categories
Rosch, E., Mervis, C. B., Gray, W. D., Johnson, D. M., & Boyes-Braem, P. (1976) · Cognitive Psychology · doi:10.1016/0010-0285(76)90013-x · Cited by 5,643 · see citing works
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Analyzing and Improving the Image Quality of StyleGAN
Karras, T., Laine, S., Aittala, M., Hellsten, J., Lehtinen, J., & Aila, T. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00813 · Cited by 6,332 · see citing works
Human-level concept learning through probabilistic program induction
Lake, B. M., Salakhutdinov, R., & Tenenbaum, J. B. (2015) · Science · doi:10.1126/science.aab3050 · Cited by 2,817 · see citing works
Building machines that learn and think like people
Lake, B. M., Ullman, T. D., Tenenbaum, J. B., & Gershman, S. J. (2017) · Behavioral and Brain Sciences · doi:10.1017/s0140525x16001837 · Cited by 2,550 · see citing works
The Structural Sources of Verb Meanings
Gleitman, L. (1990) · Language Acquisition · doi:10.1207/s15327817la0101_2 · Cited by 1,783 · see citing works
The Essential Child: Origins of Essentialism in Everyday Thought
Gelman, S. A. (2003) · doi:10.1093/acprof:oso/9780195154061.001.0001 · Cited by 1,247 · see citing works
Geirhos, R., Rubisch, P., Michaelis, C., Bethge, M., Wichmann, F. A., & Brendel, W. (2018) · arXiv · doi:10.48550/arxiv.1811.12231 · Cited by 1,490 · see citing works
“, 2014); and it is well-known that object shape is the single most important cue for human object recognition (Landau et al., 1988), much more than other cues like size or texture (which may explain the ease at which humans recognise line drawings or millennia-old cave paintings).”
BackgroundLearning words from sights and sounds: A computational model
Roy, D. K., & Pentland, A. P. (2002) · Cognitive Science · doi:10.1207/s15516709cog2601_4 · Cited by 521 · see citing works
Words as social tools: language, sociality and inner grounding in abstract concepts
Borghi, A. M., Barca, L., Binkofski, F., Castelfranchi, C., Pezzulo, G., & Tummolini, L. (2019) · Physics of Life Reviews · doi:10.1016/j.plrev.2018.12.001 · Cited by 253 · see citing works
Against stored abstractions: A radical exemplar model of language acquisition
Ambridge, B. (2020) · First Language · doi:10.1177/0142723719869731 · Cited by 185 · see citing works
Collisson, B. A., Grela, B., Spaulding, T., Rueckl, J. G., & Magnuson, J. S. (2015) · Developmental Science · doi:10.1111/desc.12219 · Cited by 65 · see citing works
Huber, L. S., Geirhos, R., & Wichmann, F. A. (2023) · Journal of Vision · doi:10.1167/jov.23.7.4 · Cited by 42 · see citing works
Development of visual object recognition
Ayzenberg, V., & Behrmann, M. (2023) · Nature Reviews Psychology · doi:10.1038/s44159-023-00266-w · Cited by 41 · see citing works
Embodied object representation learning and recognition
Van de Maele, T., Verbelen, T., Çatal, O., & Dhoedt, B. (2022) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2022.840658 · Cited by 9 · see citing works
Can You Hear Me <i>Now</i>? Sensitive Comparisons of Human and Machine Perception
Lepori, M. A., & Firestone, C. (2022) · Cognitive Science · doi:10.1111/cogs.13191 · Cited by 7 · see citing works
Burgert, T., Stoll, O., Rota, P., & Demir, B. (2025) · arXiv · doi:10.48550/arxiv.2509.20234 · Cited by 1 · see citing works
- Authors
- Landau, B., Smith, L. B., & Jones, S. S.
- Affiliations
- Columbia University (US)
- Indiana University (US)
- Corresponding author
- Landau, Barbara
- Venue
- Cognitive Development
- Publisher
- Elsevier BV
- Published
- 1988-07
- Volume
- 3
- Issue
- 3
- Pages
- 299-321
- ISSN
- 0885-2014 (ISSN-L)
- OpenAlex
- W1982374456
- Cited by
- 1,174
- References
- 1
- Citations by year
- 2026: 18 · 2025: 26 · 2024: 35 · 2023: 38 · 2022: 51 · 2021: 90 · 2020: 97 · 2019: 56 · 2018: 40 · 2017: 33 · 2016: 54 · 2015: 40 · 2014: 29 · 2013: 28 · 2012: 60
- FWCI
- 10.03
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Cognitive Development (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
- Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
- Social Sciences › Psychology › Developmental and Educational Psychology › Child and Animal Learning Development
- Keywords
- shape bias, vocabulary acquisition, word extension, perceptual similarity, perceptual categorization, count nouns, texture, size, language acquisition, early childhood, developmental changes
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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