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Humans effortlessly infer the 3D shape of objects.
Recovering intrinsic scene characteristics
Harry Barrow, J Tenenbaum, A Hanson, and E Riseman · 1978
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Recognizing imprecisely localized, partially occluded, and expression variant faces from a single sample per class
Aleix M. Martínez · 2002
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Three-dimensional shape representation in monkey cortex
Margaret E Sereno, Torsten Trinath, Mark Augath, and Nikos K Logothetis · 2002
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Hierarchical bayesian inference in the visual cortex
Tai Sing Lee and David Mumford · 2003
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Vision as Bayesian inference: analysis by synthesis?
A. Yuille and D. Kersten · 2006
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Systems in development: motor skill acquisition facilitates three-dimensional object completion
Kasey C Soska, Karen E Adolph, and Scott P Johnson · 2010
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How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, and Nicole C Rust · 2012
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Performance-optimized hierarchical models predict neural responses in higher visual cortex
Daniel LK Yamins, Ha Hong, Charles F Cadieu, Ethan A Solomon, Darren Seibert, and James J DiCarlo · 2014
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Deep supervised, but not unsupervised, models may explain it cortical representation
Seyed-Mahdi Khaligh-Razavi and Nikolaus Kriegeskorte · 2014
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Young children’s self-generated object views and object recognition
Karin H James, Susan S Jones, Linda B Smith, and Shelley N Swain · 2014
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Some views are better than others: evidence for a visual bias in object views self-generated by toddlers
Karin H James, Susan S Jones, Shelley Swain, Alfredo Pereira, and Linda B Smith · 2014
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Deep neural networks: a new framework for modeling biological vision and brain information processing
Nikolaus Kriegeskorte · 2015
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Picture : A probabilistic programming language for scene perception
Tejas D Kulkarni, Pushmeet Kohli, Joshua B Tenenbaum, and Vikash Mansinghka · 2015
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ShapeNet: An Information-Rich 3D Model Repository
Angel X. Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu · 2015
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The faces in infant-perspective scenes change over the first year of life
Swapnaa Jayaraman, Caitlin M Fausey, and Linda B Smith · 2015
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Using goal-driven deep learning models to understand sensory cortex
Daniel LK Yamins and James J DiCarlo · 2016
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Caitlin M Fausey, Swapnaa Jayaraman, and Linda B Smith · 2016
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Posterior parietal cortex drives inferotemporal activations during three-dimensional object vision
Ilse C Van Dromme, Elsie Premereur, Bram-Ernst Verhoef, Wim Vanduffel, and Peter Janssen · 2016
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Why are faces denser in the visual experiences of younger than older infants?
Swapnaa Jayaraman, Caitlin M Fausey, and Linda B Smith · 2017
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Real-world visual statistics and infants’ first-learned object names
Elizabeth M Clerkin, Elizabeth Hart, James M Rehg, Chen Yu, and Linda B Smith · 2017
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Hypernetworks
David Ha, Andrew M Dai, and Quoc V Le · 2017
Momentum contrast for unsupervised visual representation learning
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When the ventral visual stream is not enough: A deep learning account of medial temporal lobe involvement in perception
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To which out-of-distribution object orientations are dnns capable of generalizing?
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Nerf: Representing scenes as neural radiance fields for view synthesis
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Large-scale, high-resolution comparison of the core visual object recognition behavior of humans, monkeys, and state-of-the-art deep artificial neural networks
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Robert Geirhos, Patricia Rubisch, Claudio Michaelis, Matthias Bethge, Felix A Wichmann, and Wieland Brendel · 2018
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Deep convolutional networks do not classify based on global object shape
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The developing infant creates a curriculum for statistical learning
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Blender - a 3D modelling and rendering package
Blender Online Community · 2018
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Strike (with) a pose: Neural networks are easily fooled by strange poses of familiar objects
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pixelnerf: Neural radiance fields from one or few images
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Light field networks: Neural scene representations with single-evaluation rendering
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Neural fields in visual computing and beyond
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Learning online visual invariances for novel objects via supervised and self-supervised training
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Texture-like representation of objects in human visual cortex
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The neuroconnectionist research programme
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