Object Recognition: Models

Poster Session: Tuesday, May 19, 2026, 2:45 – 6:45 pm, Pavilion

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Abstract#	Poster Title	First Author
56.418	When Models See Wholes: A Mechanistic Account of Holistic Processing in Deep Vision Models	Doshi, Fenil
56.413	Three-dimensional shape cues affect human and artificial recognition systems differently	Baker, Nicholas
56.425	The SHINIER the Better: An Adaptation of the SHINE Toolbox on Python	Salvas-Hébert, Mathias
56.423	The Impact of Recurrent Circuitry on Emergent Orthogonal Category Structure in Deep Vision Models	Luo, Kexin Cindy
56.422	Task-Driven Recurrent Demands Reduce ANN Alignment with Primate IT	Fide, Ezgi
56.424	Object and Scene Recognition Abilities Predict the Content and Quality of Image Descriptions	Mueller, Melina O.
56.421	Natural shape features facilitate object representation in cortical area V4 and artificial neural networks	Wube, Dagmawi N.
56.412	Identifying the visual features of European Paleolithic cave paintings that are diagnostic of category, age, and location	Tomz, David
56.420	Exploring Individual Differences in DNN Representations	Peng, Yinuo
56.416	Critical Viewing Distance for Object Recognition under Degraded Vision	Jin, Rui
56.415	Better Models Through Worse Images: Degradation Training Helps Align CNNs with Humans	Parde, Connor
56.419	Adopting a human developmental visual diet yields robust and shape-based AI vision	Lu, Zejin
56.417	A Geometric Framework for Testing Euclidean and Hyperbolic Structure in Neural Visual Representations	Chen, Yifei E.
56.414	A deeper look into occlusion types and their impact on object recognition models	King, Courtney M.