173 citations · 204 across the 10 of their papers we have counts for
10 papers
Thinking Like an Annotator: Generation of Dataset Labeling Instructions
Nadine Chang, Francesco Ferroni, Michael J. Tarr +2
Large-scale datasets are essential to modern day deep learning. Advocates argue that understanding these methods requires dataset transparency (e.g. "dataset curation, motivation,…
Brain Diffusion for Visual Exploration: Cortical Discovery using Large Scale Generative Models
Andrew F. Luo, Margaret M. Henderson, Leila Wehbe +1
A long standing goal in neuroscience has been to elucidate the functional organization of the brain. Within higher visual cortex, functional accounts have remained relatively coars…
Quantifying the Roles of Visual, Linguistic, and Visual-Linguistic Complexity in Verb Acquisition
Yuchen Zhou, Michael J. Tarr, Daniel Yurovsky
Children typically learn the meanings of nouns earlier than the meanings of verbs. However, it is unclear whether this asymmetry is a result of complexity in the visual structure o…
TIDEE: Tidying Up Novel Rooms using Visuo-Semantic Commonsense Priors
Gabriel Sarch, Zhaoyuan Fang, Adam W. Harley +4
We introduce TIDEE, an embodied agent that tidies up a disordered scene based on learned commonsense object placement and room arrangement priors. TIDEE explores a home environment…
Learning Neural Acoustic Fields
Andrew Luo, Yilun Du, Michael J. Tarr +3
Our environment is filled with rich and dynamic acoustic information. When we walk into a cathedral, the reverberations as much as appearance inform us of the sanctuary's wide open…
AlphaNet: Improving Long-Tail Classification By Combining Classifiers
Nadine Chang, Jayanth Koushik, Aarti Singh +3
Methods in long-tail learning focus on improving performance for data-poor (rare) classes; however, performance for such classes remains much lower than performance for more data-r…
Learning Intermediate Features of Object Affordances with a Convolutional Neural Network
Aria Yuan Wang, Michael J. Tarr
Our ability to interact with the world around us relies on being able to infer what actions objects afford -- often referred to as affordances. The neural mechanisms of object-acti…
BOLD5000: A public fMRI dataset of 5000 images
Nadine Chang, John A. Pyles, Abhinav Gupta +2
Vision science, particularly machine vision, has been revolutionized by introducing large-scale image datasets and statistical learning approaches. Yet, human neuroimaging studies…
Temporal and Semantic Effects on Multisensory Integration
Jean M. Vettel, Julia R. Green, Laurie Heller +1
How do we integrate modality-specific perceptual information arising from the same physical event into a coherent percept? One possibility is that observers rely on information acr…
Estimating Learning Effects: A Short-Time Fourier Transform Regression Model for MEG Source Localization
Ying Yang, Michael J. Tarr, Robert E. Kass
Magnetoencephalography (MEG) has a high temporal resolution well-suited for studying perceptual learning. However, to identify where learning happens in the brain, one needs to ap-…