activity
20182023
most citedThe Toybox Dataset of Egocentric Visual Object Transformations

17 citations · 24 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2023★ 2 cited

A Cognitively-Inspired Neural Architecture for Visual Abstract Reasoning Using Contrastive Perceptual and Conceptual Processing

Yuan Yang, Deepayan Sanyal, James Ainooson +3

We introduce a new neural architecture for solving visual abstract reasoning tasks inspired by human cognition, specifically by observations that human abstract reasoning often int…

cs.CV2023★ 1 cited

A Computational Account Of Self-Supervised Visual Learning From Egocentric Object Play

Deepayan Sanyal, Joel Michelson, Yuan Yang +2

Research in child development has shown that embodied experience handling physical objects contributes to many cognitive abilities, including visual learning. One characteristic of…

cs.CV2023

Deep Non-Monotonic Reasoning for Visual Abstract Reasoning Tasks

Yuan Yang, Deepayan Sanyal, Joel Michelson +2

While achieving unmatched performance on many well-defined tasks, deep learning models have also been used to solve visual abstract reasoning tasks, which are relatively less well-…

cs.AI2023

A Neurodiversity-Inspired Solver for the Abstraction \& Reasoning Corpus (ARC) Using Visual Imagery and Program Synthesis

James Ainooson, Deepayan Sanyal, Joel P. Michelson +2

Core knowledge about physical objects -- e.g., their permanency, spatial transformations, and interactions -- is one of the most fundamental building blocks of biological intellige…

cs.AI2022★ 2 cited

Automatic Item Generation of Figural Analogy Problems: A Review and Outlook

Yuan Yang, Deepayan Sanyal, Joel Michelson +2

Figural analogy problems have long been a widely used format in human intelligence tests. In the past four decades, more and more research has investigated automatic item generatio…

cs.CV2020

Variable-Viewpoint Representations for 3D Object Recognition

Tengyu Ma, Joel Michelson, James Ainooson +3

For the problem of 3D object recognition, researchers using deep learning methods have developed several very different input representations, including "multi-view" snapshots take…

cs.CV2018★ 2 cited

Quantifying Human Behavior on the Block Design Test Through Automated Multi-Level Analysis of Overhead Video

Seunghwan Cha, James Ainooson, Maithilee Kunda

The block design test is a standardized, widely used neuropsychological assessment of visuospatial reasoning that involves a person recreating a series of given designs out of a se…

cs.CV2018★ 17 cited

The Toybox Dataset of Egocentric Visual Object Transformations

Xiaohan Wang, Tengyu Ma, James Ainooson +4

In object recognition research, many commonly used datasets (e.g., ImageNet and similar) contain relatively sparse distributions of object instances and views, e.g., one might see…