Face and Body Perception: Models

Poster Session: Wednesday, May 22, 2024, 8:30 am – 12:30 pm, Pavilion

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Poster Title

First Author 

1.

View-symmetric representations of faces in human and artificial neural networks

Andrews, Tim

2.

From Perception to Algorithm: Quantifying Facial Distinctiveness with a Deep Convolutional Neural Network

Boutet, Isabelle

3.

Evidence for efficient inverse graphics in the human brain using large-scale ECoG data

Calbick, Daniel

4.

Norm-referenced Encoding Supports Transfer Learning of Expressions across Strongly Different Head Shapes

Giese, Martin A.

5.

Training deep learning algorithms for face recognition with large datasets improves performance but reduces similarity to human representations

Guy, Nitzan

6.

FaReT 2.1: Anatomically precise manipulation of race in 3D face models and a pipeline to import real face scans

Martin, Emily

7.

Reading minds in the eyes with GPT4-vision

Murray, Scott

8.

Modeling face-Identity “likeness” with a convolutional neural network trained for face identification

Parde, Connor J.

9.

Bayesian adaptive estimation of high-dimensional psychometric functions: A particle filtering approach

Reining, Lars

10.

Visualizing the Other-Race Effect with GAN-based Image Reconstruction

Shoura, Moaz

11.

Efficient Inverse Graphics with Differentiable Generative Models Explains Trial-level Face Discriminations and Robustness of Face Perception to Unusual Viewing Angles

Yilmaz, Hakan