The DOI matches its Crossref record; 158 of the 159 references it cites were found in a registry or an index.
Object Perception as Bayesian Inference
Open accessAbstract
We perceive the shapes and material properties of objects quickly and reliably despite the complexity and objective ambiguities of natural images. Typical images are highly complex because they consist of many objects embedded in background clutter. Moreover, the image features of an object are extremely variable and ambiguous owing to the effects of projection, occlusion, background clutter, and illumination. The very success of everyday vision implies neural mechanisms, yet to be understood, that discount irrelevant information and organize ambiguous or noisy local image features into objects and surfaces. Recent work in Bayesian theories of visual perception has shown how complexity may be managed and ambiguity resolved through the task-dependent, probabilistic integration of prior object knowledge with image features.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“GNW neurons, lying at the top of a deep feedforward network, provide a compressed, high-level symbolic model of an aspect of the external world; top-down signals broadcast the predictions that this model makes to lower-level areas; and bottom-up signals convey sensory signals and may either amplify the signals predicted by top-down input”
From Conscious Processing and the Global Neuronal Workspace Hypothesis (2020) · cites this paper as Kersten et al., 2004
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“The product of the likelihood and prior-the posterior distribution over scenes, given the image y 0 -thus strongly favors some scene interpretations over others”
From The Interface Theory of Perception (2015) · cites this paper as Kersten, Mamassian & Yuille, 2004
The cited source says what the claim attributes to it.
In the citing paper
“Interestingly, human observers often approach such an 'ideal observer' ([102], but see [103]), inspiring the idea that the human perceptual system may implement (approximate) Bayesian inference [104].”
From How Do Expectations Shape Perception? (2018) · cites this paper as [104]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“These two mechanisms, which have been referred to as 'shutting up' and 'stop gossiping' [4,104] (see also previous paragraph on dampening vs sharpening) are both accommodated within predictive coding, and operate on distinct populations (error and prediction units, respectively).”
From How Do Expectations Shape Perception? (2018) · cites this paper as [104]
The cited source says what the claim attributes to it.
In the citing paper
“Disentangling the many external states that could underlie any given sensory input is an ill-posed inverse problem that requires constraints or regularization (e.g., by the priors of a generative model; Lee and Mumford, 2003; Kersten et al., 2004).”
From Allostatic Self-efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression (2016) · cites this paper as Kersten et al., 2004
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Wu, Y., & Vapnik, V. N. (1999) · Technometrics · doi:10.2307/1271368 · Cited by 27,236
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162
(1988) · Cited by 16,582
Robust Real-Time Face Detection
Viola, P., & Jones, M. J. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000013087.49260.fb · Cited by 14,097
Schölkopf, B., & Smola, A. J. (2001) · The MIT Press eBooks · doi:10.7551/mitpress/4175.001.0001 · Cited by 11,934
(1966) · Medical Entomology and Zoology · Cited by 10,293
Signal detection theory and psychophysics
Ingleby, D. (1967) · Journal of Sound and Vibration · doi:10.1016/0022-460x(67)90197-6 · Cited by 8,616
Statistical Decision Theory and Bayesian Analysis
Berger, J. O. (1985) · Springer Series in Statistics · doi:10.1007/978-1-4757-4286-2 · Cited by 7,722
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
Oliva, A., & Torralba, A. B. (2001) · International Journal of Computer Vision · doi:10.1023/a:1011139631724 · Cited by 6,321
Rao, R. P. N., & Ballard, D. H. (1999) · Nature Neuroscience · doi:10.1038/4580 · Cited by 5,483 · cited 2×
“…depth, or background clutter) may require an internal generative process that in some sense mirrors aspects of the external generative model used for inference (Grenander 1996, Mumford 1992,Rao & Ballard 1999,Tu & Zhu 2002a,Tu et al 2003) or for learning (Dayan et al 1995,Hinton & Ghahramani 1997).”
Background
Research works printed but not linked: 5
- Bülthoff HH, 1991, Comments Theor. Biol., 2, 283
- Freund Y, 1999, J. Jpn. Soc. Artif. Intell., 14, 771
- Kanizsa G, 1976, Vision and Artifact
- Konishi SM, 2003, Pattern Anal. Mach. Intell., 1, 37
- Tu Z, Chen A, Yuille AL, Zhu SC. 2003. Image parsing. Proc. Int. Conf. Comput. Vis. , Cannes, France
Cited by
Sorted by citations
Items 401–500 of 1,000
Time-dependent discrimination advantages for harmonic sounds suggest efficient coding for memory
McPherson, M. J., & McDermott, J. H. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2008956117 · Cited by 35
Aberrant causal inference and presence of a compensatory mechanism in autism spectrum disorder
Noel, J., Shivkumar, S., Dokka, K., Haefner, R. M., & Angelaki, D. E. (2022) · eLife · doi:10.7554/elife.71866 · Cited by 36
Bayesian Models of Brain and Behaviour
Penny, W. D. (2012) · ISRN Biomathematics · doi:10.5402/2012/785791 · Cited by 38
Learning Through Time in the Thalamocortical LoopsPreprint
O’Reilly, R. C., Wyatte, D., & Rohrlich, J. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1407.3432 · Cited by 36
Gilet, E., Diard, J., & Bessìère, P. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020387 · Cited by 40
Human noise blindness drives suboptimal cognitive inference
Castañón, S. H., Moran, R., Ding, J., Egner, T., Bang, D., & Summerfield, C. (2019) · Nature Communications · doi:10.1038/s41467-019-09330-7 · Cited by 34
A neural mechanism for contextualizing fragmented inputs during naturalistic vision
KAISER, D. H., Turini, J., & Cichy, R. M. (2019) · eLife · doi:10.7554/elife.48182 · Cited by 34
Neural implementations of Bayesian inference
Sohn, H., & Narain, D. (2021) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2021.09.008 · Cited by 37
Why Do Only Some Hyperopes Become Strabismic?
Babinsky, E. E., & Candy, T. R. (2013) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.12-10670 · Cited by 34
Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models
Beck, J. M., Pouget, A., & Heller, K. (2012) · Archive ouverte UNIGE (University of Geneva) · Cited by 34
Huang, H. (2017) · Journal of Statistical Mechanics Theory and Experiment · doi:10.1088/1742-5468/aa6ddc · Cited by 35
Binocular shape constancy from novel views: The role of a priori constraints
Chan, M. W., Stevenson, A. K., Li, Y., & Pizlo, Z. (2006) · Perception & Psychophysics · doi:10.3758/bf03193715 · Cited by 34
Body Actions Change the Appearance of Facial Expressions
Fantoni, C., & Gerbino, W. (2014) · PLoS ONE · doi:10.1371/journal.pone.0108211 · Cited by 35
Perceptual Integration for Qualitatively Different 3-D Cues in the Human Brain
Dövencioğlu, D. N., Ban, H., Schofield, A. J., & Welchman, A. E. (2013) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00417 · Cited by 33
Smith, R. S., Weihs, K. L., Alkozei, A., Killgore, W. D. S., & Lane, R. D. (2018) · Psychosomatic Medicine · doi:10.1097/psy.0000000000000661 · Cited by 35
Within- and Cross-Modal Distance Information Disambiguate Visual Size-Change Perception
Battaglia, P., Luca, M. D., Ernst, M. O., Schrater, P., Machulla, T., & Kersten, D. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000697 · Cited by 34
Self-citationLaurence, S., & Margolis, E. (2005) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195179675.003.0013 · Cited by 33
Simpson, T., Carruthers, P., Laurence, S., & Stich, S. (2005) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195179675.003.0001 · Cited by 34
Kim, H. R., Pitkow, X., Angelaki, D. E., & DeAngelis, G. C. (2016) · Journal of Neurophysiology · doi:10.1152/jn.00005.2016 · Cited by 32
A tutorial on Bayesian models of perception
Vincent, B. T. (2015) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2015.02.001 · Cited by 35
Spontaneous Activity Patterns in Primary Visual Cortex Predispose to Visual Hallucinations
Pajani, A., Kok, P., Kouider, S., & de Lange, F. P. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.1520-15.2015 · Cited by 35
Multisensory Oddity Detection as Bayesian Inference
Hospedales, T. M., & Vijayakumar, S. (2009) · PLoS ONE · doi:10.1371/journal.pone.0004205 · Cited by 33
A hierarchical model for automatic nuchal translucency detection from ultrasound images
Deng, Y., Wang, Y., Chen, P., & Yu, J. (2012) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2012.04.002 · Cited by 31
Perception as an Inference Problem
Olshausen, B. A. (2014) · The MIT Press eBooks · doi:10.7551/mitpress/9504.003.0037 · Cited by 31
Belief digitization: Do we treat uncertainty as probabilities or as bits?
Johnson, S. G. B., Merchant, T., & Keil, F. C. (2019) · Journal of Experimental Psychology General · doi:10.1037/xge0000720 · Cited by 31
Causal inference in environmental sound recognition
Traer, J. A., Norman-Haignere, S., & McDermott, J. H. (2021) · Cognition · doi:10.1016/j.cognition.2021.104627 · Cited by 31
An implicit representation of stimulus ambiguity in pupil size
Graves, J. E., Égré, P., Pressnitzer, D., & de Gardelle, V. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2107997118 · Cited by 32
Multisensory decisions from self to world
Zaidel, A., & Salomon, R. (2023) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2022.0335 · Cited by 32
Park, I. M., & Pillow, J. W. (2026) · PLoS Computational Biology · doi:10.1101/178418 · Cited by 31
Perceptual inference employs intrinsic alpha frequency to resolve perceptual ambiguity
Shen, L., Han, B., Chen, L., & Chen, Q. (2019) · PLoS Biology · doi:10.1371/journal.pbio.3000025 · Cited by 31
Active Inference and Cognitive Consistency
Friston, K. J. (2018) · Psychological Inquiry · doi:10.1080/1047840x.2018.1480693 · Cited by 34
Probabilistic rejection templates in visual working memory
Четвериков, А. А., Campana, G., & Kristjansson, A. K. (2019) · Cognition · doi:10.1016/j.cognition.2019.104075 · Cited by 30
Brass Tacks in Linguistic Theory
Crain, S., Gualmini, A., & Pietroski, P. M. (2005) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195179675.003.0011 · Cited by 30
The hypothesis testing brain: some philosophical applications
Hohwy, J. (2010) · Conference of the Australasian Society for Cognitive Science · doi:10.5096/ascs200922 · Cited by 35
Implicit and explicit processes in category-based induction: Is induction best when we don’t think?
Chen, S. Y., Ross, B. H., & Murphy, G. L. (2013) · Journal of Experimental Psychology General · doi:10.1037/a0032064 · Cited by 31
Innateness and (Bayesian) Visual Perception
Scholl, B. J. (2005) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195179675.003.0003 · Cited by 31
A neural implementation of Bayesian inference based on predictive coding
Spratling, M. (2016) · Connection Science · doi:10.1080/09540091.2016.1243655 · Cited by 32
Complex Probabilistic Inference
Gershman, S. J., & Beck, J. M. (2017) · Wiley eBooks · doi:10.1002/9781119159193.ch33 · Cited by 30
Pattern completion and disruption characterize contextual modulation in the visual cortexPreprint
Fu, J., Shrinivasan, S., Baroni, L., Ding, Z., Fahey, P. G., Pierzchlewicz, P. A., Ponder, K., Froebe, R., Ntanavara, L., Muhammad, T., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.03.13.532473 · Cited by 33
Sampling-based Bayesian inference in recurrent circuits of stochastic spiking neurons
Zhang, W., Wu, S., Josić́, K., & Doiron, B. (2023) · Nature Communications · doi:10.1038/s41467-023-41743-3 · Cited by 31
Schettino, A., Loeys, T., Delplanque, S., & Pourtois, G. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.009 · Cited by 34
Attention directed by expectations enhances receptive fields in cortical area MT
Ghose, G. M., & Bearl, D. W. (2009) · Vision Research · doi:10.1016/j.visres.2009.10.003 · Cited by 29
A Bayesian approach to person perception
Clifford, C. W. G., Mareschal, I., Otsuka, Y., & Watson, T. (2015) · Consciousness and Cognition · doi:10.1016/j.concog.2015.03.015 · Cited by 29
Bayesian Models of Perceptual Organization
Feldman, J. (2014) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780199686858.013.007 · Cited by 29
Three-dimensional displays and stereo vision
Westheimer, G. (2011) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2010.2777 · Cited by 29
Erdogan, G., Yildirim, I., & Jacobs, R. A. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004610 · Cited by 29
The radiology task: Bayesian theory and perception
Donovan, T., & Manning, D. (2007) · British Journal of Radiology · doi:10.1259/bjr/98148548 · Cited by 29
Shape, perspective, and what is and is not perceived: Comment on Morales, Bax, and Firestone (2020).
Burge, J., & Burge, T. (2022) · Psychological Review · doi:10.1037/rev0000363 · Cited by 28
A Computational Account of the Development and Evolution of Psychotic Symptoms
Powers, A. R., Angelos, P. A., Bond, A., Farina, E., Fredericks, C. A., Gandhi, J., Greenwald, M. S., Hernández-Busot, G., Hosein, G. X., Kelley, M., et al. (2024) · Biological Psychiatry · doi:10.1016/j.biopsych.2024.08.026 · Cited by 29
Belief states as a framework to explain extra-retinal influences in visual cortex
Nienborg, H., & Roelfsema, P. R. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2014.10.013 · Cited by 29
Pursuing motion illusions: A realistic oculomotor framework for Bayesian inference
Bogadhi, A. R., Montagnini, A., Mamassian, P., Perrinet, L., & Masson, G. S. (2010) · Vision Research · doi:10.1016/j.visres.2010.10.021 · Cited by 28
Self-citationOpposite Modulation of High- and Low-Level Visual Aftereffects by Perceptual Grouping
He, D., Kersten, D., & Fang, F. (2012) · Current Biology · doi:10.1016/j.cub.2012.04.026 · Cited by 28
Self-citationExplicit estimation of visual uncertainty in human motion processing
Graf, E. W., Warren, P. A., & Maloney, L. T. (2005) · Vision Research · doi:10.1016/j.visres.2005.08.007 · Cited by 29
Can circular inference relate the neuropathological and behavioral aspects of schizophrenia?
Leptourgos, P., Denève, S., & Jardri, R. (2017) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2017.08.012 · Cited by 28
Tabor, A., Ryckeghem, D. M. L. V., & Hasenbring, M. I. (2019) · Clinical Journal of Pain · doi:10.1097/ajp.0000000000000786 · Cited by 28
Embodied AI: A Survey on the Evolution from Perceptive to Behavioral Intelligence
Yifan, C., Wei, M., Wang, X., Liu, Y., Wang, J., Song, H., Ma, L., Di, D., Sun, C., Liu, K., et al. (2025) · SmartBot · doi:10.1002/smb2.70003 · Cited by 30
Backus, B. T. (2009) · Journal of Vision · doi:10.1167/9.1.6 · Cited by 27
Bayesian Cue Integration as a Developmental Outcome of Reward Mediated Learning
Weisswange, T. H., Rothkopf, C. A., Rodemann, T., & Triesch, J. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021575 · Cited by 29
Explaining away results in accurate and tolerant template matching
Spratling, M. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2020.107337 · Cited by 27
Segil, J. L., Cuberovic, I., Graczyk, E. L., Weir, R. F. F., & Tyler, D. J. (2020) · Scientific Reports · doi:10.1038/s41598-020-62970-4 · Cited by 28
Evidence of Serial Dependence from Decoding of Visual Evoked Potentials
Ranieri, G., Benedetto, A., Ho, H. T., Burr, D. C., & Morrone, M. C. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.1879-21.2022 · Cited by 27
Prior information differentially affects discrimination decisions and subjective confidence reports
Constant, M., Pereira, M., Faivre, N., & Filevich, E. (2023) · Nature Communications · doi:10.1038/s41467-023-41112-0 · Cited by 27
The influence of shape cues on the perception of lighting direction
O'Shea, J. P., Agrawala, M., & Banks, M. S. (2010) · Journal of Vision · doi:10.1167/10.12.21 · Cited by 27
Human Sound Source Identification
Lutfi, R. A. (2007) · Springer handbook of auditory research · doi:10.1007/978-0-387-71305-2_2 · Cited by 27
Auditory Perception: Laurel and Yanny Together at Last
Pressnitzer, D., Graves, J. E., Chambers, C., de Gardelle, V., & Égré, P. (2018) · Current Biology · doi:10.1016/j.cub.2018.06.002 · Cited by 27
Naturalizing Phenomenology: A Must Have?
Albertazzi, L. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.01933 · Cited by 31
Bayesian data analysis as a tool for behavior analysts
Young, M. E. (2019) · Journal of the Experimental Analysis of Behavior · doi:10.1002/jeab.512 · Cited by 30
Adaptation of the human visual system to the statistics of letters and line configurations
Chang, C. H. C., Pallier, C., Wu, D. H., Nakamura, K., Jobert, A., Kuo, W., & Dehaene, S. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.07.028 · Cited by 30
Inconsistency of perceived 3D shape
Luca, M. D., Domini, F., & Caudek, C. (2010) · Vision Research · doi:10.1016/j.visres.2010.05.006 · Cited by 27
Perceived object trajectories during occlusion constrain visual statistical learning
Fiser, J., Scholl, B., & Aslin, R. (2007) · Psychonomic Bulletin & Review · doi:10.3758/bf03194046 · Cited by 25
Brain-inspired Bayesian perception for biomimetic robot touch
Lepora, N. F., Sullivan, J. C., Mitchinson, B., Pearson, M. J., GURNEY, K. N., & Prescott, T. J. (2012) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2012.6224815 · Cited by 26
Zhong, S.-H., Ma, Z., Wilson, C., Liu, Y., & Flombaum, J. I. (2014) · Journal of Vision · doi:10.1167/14.12.12 · Cited by 26
Color Afterimages in Autistic Adults
Maule, J., Stanworth, K., Pellicano, E., & Franklin, A. (2016) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-016-2786-5 · Cited by 26
Experience-Driven Auditory Attention
Addleman, D. A., & Jiang, Y. V. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.08.002 · Cited by 26
Serial dependence for oculomotor control depends on early sensory signals
Goettker, A., & Stewart, E. E. M. (2022) · Current Biology · doi:10.1016/j.cub.2022.05.011 · Cited by 26
The close proximity of threat: altered distance perception in the anticipation of pain
Tabor, A., Catley, M. J., Gandevia, S. C., Thacker, M. A., Spence, C. J., & Moseley, G. L. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00626 · Cited by 26
Bayet, L., Pascalis, O., & Gentaz, É. (2014) · L’Année psychologique · doi:10.4074/s0003503314003030 · Cited by 40
Zhang, R., Kwon, O., & Tadin, D. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.4744-12.2013 · Cited by 26
The Discovery of Common-Sense Psychology
Reisenzein, R., & Rudolph, U. (2008) · Social Psychology · doi:10.1027/1864-9335.39.3.125 · Cited by 28
Backus, B. T., & Qi, H. (2007) · Vision Research · doi:10.1016/j.visres.2006.12.008 · Cited by 26
Ellis, G. (2018) · Physics of Life Reviews · doi:10.1016/j.plrev.2018.05.006 · Cited by 25
Inference of perceptual priors from path dynamics of passive self-motion
Prsa, M., Jimenez-Rezende, D., & Blanke, O. (2014) · Journal of Neurophysiology · doi:10.1152/jn.00755.2014 · Cited by 28
Automated detection of fetal nuchal translucency based on hierarchical structural model
Deng, Y., Wang, Y., & Chen, P. (2010) · Proceedings - IEEE Symposium on Computer-Based Medical Systems · doi:10.1109/cbms.2010.6042618 · Cited by 25
Sound Location Can Influence Audiovisual Speech Perception When Spatial Attention Is Manipulated
Möttönen, R., Tiippana, K. M., Sams, M. E., & Puharinen, H. (2011) · Seeing and Perceiving · doi:10.1163/187847511x557308 · Cited by 27
Responses in early visual areas to contour integration are context dependent
Qiu, C., Burton, P. C., Kersten, D., & Olman, C. A. (2016) · Journal of Vision · doi:10.1167/16.8.19 · Cited by 25
Self-citationNeural Mechanisms for Perceptual Decision Making
Gold, J. I., & Heekeren, H. R. (2013) · Elsevier eBooks · doi:10.1016/b978-0-12-416008-8.00019-x · Cited by 29
Short-term and long-term attentional biases to frequently encountered target features
Sha, L. Z., Remington, R. W., & Jiang, Y. V. (2017) · Attention Perception & Psychophysics · doi:10.3758/s13414-017-1317-6 · Cited by 25
Kornmeier, J., Wörner, R., Riedel, A., & van Elst, L. T. (2017) · PLoS ONE · doi:10.1371/journal.pone.0189197 · Cited by 25
Affective certainty and congruency of touch modulate the experience of the rubber hand illusion
Filippetti, M. L., Kirsch, L. P., Crucianelli, L., & Fotopoulou, A. (2019) · Scientific Reports · doi:10.1038/s41598-019-38880-5 · Cited by 27
Trujillo, L. T. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.01292 · Cited by 27
Michel, M. M., & Jacobs, R. A. (2007) · Journal of Vision · doi:10.1167/7.1.4 · Cited by 26
Saddler, M. R., & McDermott, J. H. (2024) · Nature Communications · doi:10.1038/s41467-024-54700-5 · Cited by 24
Harmonic Cancellation—A Fundamental of Auditory Scene Analysis
Alain De Cheveigné, A. (2021) · Trends in Hearing · doi:10.1177/23312165211041422 · Cited by 24
Normative Principles for Decision-Making in Natural Environments
Summerfield, C., & Parpart, P. (2021) · Annual Review of Psychology · doi:10.1146/annurev-psych-020821-104057 · Cited by 26
Adaptive oscillators support Bayesian prediction in temporal processing
Doelling, K. B., Arnal, L. H., & Assaneo, M. F. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011669 · Cited by 24
Early influence of prior experience on face perception
Gamond, L., George, N., Lemaréchal, J.-D., Hugueville, L., Adam, C., & Tallon‐Baudry, C. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.08.081 · Cited by 28
Optical superresolution and visual hyperacuity
Westheimer, G. (2012) · Progress in Retinal and Eye Research · doi:10.1016/j.preteyeres.2012.05.001 · Cited by 24
A Bayesian model of lightness perception that incorporates spatial variation in the illumination
Allred, S., & Brainard, D. H. (2013) · Journal of Vision · doi:10.1167/13.7.18 · Cited by 24
Interactions Between Apparent Motion Rivalry in Vision and Touch
Conrad, V., Vitello, M. P., & Noppeney, U. (2012) · Psychological Science · doi:10.1177/0956797612438735 · Cited by 24
Alabi, D., & Wu, E. (2016) · Workshop on Human-In-the-Loop Data Analytics (HILDA) · doi:10.1145/2939502.2939512 · Cited by 24
Metadata
- Authors
- Kersten, D., Mamassian, P., & Yuille, A.
- Affiliations
- University of Minnesota (US)
- University of Glasgow (GB)
- University of California, Los Angeles (US)
- Venue
- Annual Review of Psychology
- Publisher
- Annual Reviews
- Published
- 2004-02-01
- Volume
- 55
- Issue
- 1
- Pages
- 271-304
- ISSN
- 0066-4308 (ISSN-L)
- 1545-2085
- OpenAlex
- W1497935377
- Cited by
- 1,269
- References
- 159
- Citations by year
- 2026: 33 · 2025: 55 · 2024: 45 · 2023: 49 · 2022: 63 · 2021: 53 · 2020: 71 · 2019: 97 · 2018: 71 · 2017: 60 · 2016: 78 · 2015: 70 · 2014: 69 · 2013: 57 · 2012: 52
- FWCI
- 3.33
- Type
- journal article
- Language
- en
- Open access
- green
- escholarship.org
- Locations
- Annual Review of Psychology (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Department of Statistics, UCLA
- Funders
- National Institutes of Health (5r01ey011507-04, 5r01ey012691-03)
- National Eye Institute (R01EY013875, EY12691, R01 EY11507-001, EY013875, EY02587)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Keywords
- object perception, Bayesian inference, prior knowledge, probabilistic integration, object shape perception, occlusion, background clutter, illumination effects
- MeSH terms
- Bayes Theorem, Decision Making, Humans, Learning, Psychological Theory, Psychophysics, Visual Perception
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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
