Object permanence in five-month-old infants.

By Furth Hg. 1987

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Citations in the corpus

On the Binding Problem in Artificial Neural Networks (2020, background): “…analogical thinking, etc. Human understanding of the world in terms of objects develops at an early age (Spelke and Kinzler, 2007) and infants as young as five months appear to understand that objects continue to exist in the absence of visual stimuli (object permanence; Baillargeon et al., 1985).”
PIP: Physical Interaction Prediction via Mental Imagery with Span Selection (2021, background): “The first category of AI approaches [6, 7, 8] draws inspiration from developmental psychology research, which centers around the notion that humans acquire a general physical understanding of the world through an intuitive physics engine within our cognition [9, 10, 6, 11].”
Revealing Occlusions with 4D Neural Fields (2022, background): “In several studies, developmental psychologists have been able to demonstrate that shortly after birth, children learn how objects persist during occlusions [2, 5, 42, 52], and evidence suggests that animals perform similar reasoning too [32, 41].”
Grounding the Lexical Semantics of Verbs in Visual Perception using Force Dynamics and Event Logic (1999, background): “Furthermore, two objects on the same layer must obey thesubstantiality constraint, the constraint that they not interpenetrate (Spelke, 1983; Baillargeon et al., 1985; Baillargeon, 1986, 1987; Spelke, 1987, 1988).”
Identification of objects in 9‐month‐old infants: integrating ‘what’ and ‘where’ information (2003, unknown): “Baillargeon, 1986, 1987; Baillargeon, Spelke & Wasserman, 1985; Leslie & Keeble, 1987; Spelke, 1988, 1994; Spelke, Breinlinger, Macomber & Jacobson, 1992).”
R-SQAIR: Relational Sequential Attend, Infer, Repeat (2019, background): “1 Introduction Numerous studies [35, 17, 27, 1, 22] show that infants quickly develop an understanding of intuitive physics, objects and relations in an unsupervised manner.”
Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense (2020, background): “Other studies have shown that humans are highly sensitive to whether objects in a scene violate certain understood physical relationships or appear to be physical unstable [91, 92, 93, 94, 95].”
Physion: Evaluating Physical Prediction from Vision in Humans and Machines (2021, background): “The second type of prediction algorithm has been inspired by human development research and cognitive science, which has shown that infants acquire general physical understanding of objects and their behavior early in life [4, 60, 15, 5] and that adults may “simulate” how scenes will evolve accordin”
Holistic++ Scene Understanding: Single-View 3D Holistic Scene Parsing and Human Pose Estimation With Human-Object Interaction and Physical Commonsense (2019, background): “ing occlusions [43, 20], tracking small objects even if contained by other objects [10], realizing object permanence [2], recognizing rational HOI [46, 37], understanding intuitive physic [11, 29, 1], and using exploratory play to understand the environment [42].”