Simon M. Hofmann
@smnhfmnn.bsky.social
Research in XAI @ Max Plack Institute for Human Cognitive & Brain Sciences (MPI CBS) | in the cinema @ Berlinale Generation
Despite these similarities, subtle differences emerged:
Features like chin-cheek distance, eye size, nose shape 🤥, and face-width-height ratio (especially in 3D) explained much of the variance in the human judgments.
(image: DALL-E)
(4/n)
Features like chin-cheek distance, eye size, nose shape 🤥, and face-width-height ratio (especially in 3D) explained much of the variance in the human judgments.
(image: DALL-E)
(4/n)
November 13, 2024 at 2:59 PM
Despite these similarities, subtle differences emerged:
Features like chin-cheek distance, eye size, nose shape 🤥, and face-width-height ratio (especially in 3D) explained much of the variance in the human judgments.
(image: DALL-E)
(4/n)
Features like chin-cheek distance, eye size, nose shape 🤥, and face-width-height ratio (especially in 3D) explained much of the variance in the human judgments.
(image: DALL-E)
(4/n)
Our results showed a strong correlation between 2D and 3D viewing conditions, indicating consistent processing of face similarity across dimensions.
However, ...
(3/n)
However, ...
(3/n)
November 13, 2024 at 2:59 PM
Our results showed a strong correlation between 2D and 3D viewing conditions, indicating consistent processing of face similarity across dimensions.
However, ...
(3/n)
However, ...
(3/n)
We employed a triplet odd-one-out task (🥸,🤓,😎) and distributed it online to thousands of participants.
We then trained sparse (#VICE, @lukasmut.bsky.social) and deep encoding models (#VGG-Face) to investigate the latent representations underlying human face similarity judgments.
#alignment
(2/n)
We then trained sparse (#VICE, @lukasmut.bsky.social) and deep encoding models (#VGG-Face) to investigate the latent representations underlying human face similarity judgments.
#alignment
(2/n)
November 13, 2024 at 2:59 PM
We employed a triplet odd-one-out task (🥸,🤓,😎) and distributed it online to thousands of participants.
We then trained sparse (#VICE, @lukasmut.bsky.social) and deep encoding models (#VGG-Face) to investigate the latent representations underlying human face similarity judgments.
#alignment
(2/n)
We then trained sparse (#VICE, @lukasmut.bsky.social) and deep encoding models (#VGG-Face) to investigate the latent representations underlying human face similarity judgments.
#alignment
(2/n)
We are happy to share our new paper (under review) on human face perception!
In this study, we investigated how face similarity judgments are affected by dynamic 3D vs. static 2D conditions 🗿.
Preprint: doi.org/10.31234/osf...
#FacePerception #3D #CognitiveScience #similarity #NeuroAI
(1/n)
In this study, we investigated how face similarity judgments are affected by dynamic 3D vs. static 2D conditions 🗿.
Preprint: doi.org/10.31234/osf...
#FacePerception #3D #CognitiveScience #similarity #NeuroAI
(1/n)
November 13, 2024 at 2:59 PM
We are happy to share our new paper (under review) on human face perception!
In this study, we investigated how face similarity judgments are affected by dynamic 3D vs. static 2D conditions 🗿.
Preprint: doi.org/10.31234/osf...
#FacePerception #3D #CognitiveScience #similarity #NeuroAI
(1/n)
In this study, we investigated how face similarity judgments are affected by dynamic 3D vs. static 2D conditions 🗿.
Preprint: doi.org/10.31234/osf...
#FacePerception #3D #CognitiveScience #similarity #NeuroAI
(1/n)
