The Ecological Approach to Visual Perception: Classic Edition

By J. Gibson. 2014

2,005 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/1054b9480d759485cc4573f16b4537c698ba26d2

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In Cognitive Neuroscience

Citations in the corpus

The impact of greening schoolyards on the appreciation, and physical, cognitive and social-emotional well-being of schoolchildren: A prospective intervention study (2018, background): “In the light of Affordance Theory (Gibson, 1979), these findings could be explained by Fjørtoft et al.”
UniSim: A Neural Closed-Loop Sensor Simulator (2023, background): “But to enable end-to-end testing of full autonomy systems, we must also simulate realistic sensor observations of the 3D environment for the robot to perceive, interact with its surroundings, and plan accordingly [19].”
CLIPort: What and Where Pathways for Robotic Manipulation (2021, background): “This action-centric approach to perception [19] is data efficient and effective at circumventing the need for explicit “objectness” in learnt representations.”
Perceiver-Actor: A Multi-Task Transformer for Robotic Manipulation (2022, methodology): “This voxel-based formulation provides a strong structural prior with several benefits: a natural method for fusing multi-view observations, learning robust action-centric3 representations [17], and enabling data augmentation in 6-DoF – all of which help learn generalizable skills by focusing on dive”
Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age (2016, neutral): “obal pose of the car as a whole in a single and efﬁcient operation as opposed to update, for 4The term affordances refers to the set of possible actions on a given object/environment by a given agent [110]. While the term actionability includes the expected utility of these actions. 5Reasoning in th”
Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense (2020, background): “st effect [472] has been proven to be one of the key ingredients in relational and analogical reasoning for both human and machine learning [473,474,475,476,477]. Originating from perceptual learning [478,479], it is well established in the ﬁeld of psychology and education [480,481,482,483,484] that”
Hierarchical visuomotor control of humanoids (2018, background): “The visual features that this analysis identiﬁes correspond roughly to sensorimotor affor-dances (Gibson, 2014); the agent’s perceptual representations were shaped by goals and action.”
V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning (2025, neutral): “While such tasks have served to drive progress, it remains an important goal of a visual system to enable an agent to interact with the physical world (Gibson, 1979).”
Visual Semantic Planning Using Deep Successor Representations (2017, methodology): “We categorize the objects by their affordances [15], i.”
Learning Visual Affordances for Robotic Manipulation (2019, background): “Gibson, who theorized that animals (including humans) could directly perceive the environment by what it has to offer them [31].”
KETO: Learning Keypoint Representations for Tool Manipulation (2019, background): “intelligence in cognitive science studies [4], [3], [42], [19].”
Grounded Human-Object Interaction Hotspots From Video (2018, background): “Gibson’s theory of affordances [17] provides a way to reason about object function.”
DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics (2020, positive): “In other words, a relevance map implements an affordance [71].”
Learning Affordance Landscapes for Interaction Exploration in 3D Environments (2020, background): “Visual affordances An affordance is the potential for action [22].”
Investigating Human Priors for Playing Video Games (2018, background): “Here, the platforms and ladders afford the actions of walking and climbing (Gibson, 2014), irrespective of their appearance.”