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AVoE: A Synthetic 3D Dataset on Understanding Violation of Expectation for Artificial Cognition
Arijit Dasgupta · Jiafei Duan · Marcelo Ang Jr · Cheston Tan

Tue Dec 14 11:12 AM -- 11:14 AM (PST) @

Recent work in cognitive reasoning and computer vision has engendered an increasing popularity for the Violation-of-Expectation (VoE) paradigm in synthetic datasets. Inspired by work in infant psychology, researchers have started evaluating a model's ability to discriminate between expected and surprising scenes as a sign of its reasoning ability. Existing VoE-based 3D datasets in physical reasoning only provide vision data. However, current cognitive models of physical reasoning by psychologists reveal infants create high-level abstract representations of objects and interactions. Capitalizing on this knowledge, we propose AVoE: a synthetic 3D VoE-based dataset that presents stimuli from multiple novel sub-categories for five event categories of physical reasoning. Compared to existing work, AVoE is armed with ground-truth labels of abstract features and rules augmented to vision data, paving the way for high-level symbolic predictions in physical reasoning tasks.

Author Information

Arijit Dasgupta (National University of Singapore)
Jiafei Duan (Institute for Infocomm Research, Singapore)
Marcelo Ang Jr (National University of Singapore)
Cheston Tan (Institute for Infocomm Research, Singapore)

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