Visual Analogy Between Object Parts

Lu, Hongjing

A study of humans and convolutional neural networks on how to recognize blurry objects at the threshold of visibility

Jang, Hojin

Evaluating machine comprehension of sketch meaning at different levels of abstraction

Lu, Xuanchen

Face-deprived networks show distributed but not clustered face-selective maps

Doshi, Fenil R.

Feature Visualizations do not sufficiently explain hidden units of Artificial Neural Networks

Klein, Thomas

Is it always computationally advantageous to use segregated pathways to process different visual stimulus attributes separately?

Han, Zhixian

Language Models of Visual Cortex: Where do they work? And why do they work so well where they do?

Conwell, Colin

Phase-Dependent Asymmetry of Pattern Masking in Natural Images Explained by Intrinsic Position Uncertainty

Zhang, Anqi

Statistical inference on representational geometries

Schütt, Heiko

The role of scene context in object recognition by humans and convolutional neural networks

Frey, Haley G.

Uncovering high-level visual cortex preferences by training convolutional neural networks on large neuroimaging data

Seeliger, K.

Visual angle and image context alter the alignment between deep convolutional neural networks and the macaque ventral stream

Djambazovska, Sara

Predicting human camouflage detection with a principled computational model

Das, Abhranil

A Generalized Framework for Optimizing and Informing the Implementation of QUEST

Duwell, Ethan

Top-down and within-layer recurrent connections in artificial networks are needed to solve challenging visual tasks

Costantino, Andrea Ivan