Hidden Layers: An Interactive Installation for Exploring the Neural Semantics of Image Synthesis

Figure 1: A visualization of the hidden layers of our GAN-based prototype generating fashion imagery.Normally concealed within the black box of a generative model, this visualization reveals the activation of the hidden layers-progressing from left to right-consisting of many channels, here visualized as grids of neurons.Magenta pixels indicate positive, while cyan pixels represent negative activation of a neuron.We explore their material properties as a new modality for interaction.

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Published
2025-08-18
DOI
https://doi.org/10.1145/3737609.3747108
Primary Topic
Image Retrieval and Classification Techniques
Type
article
Field-Weighted Citation Impact
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article

Hidden Layers: An Interactive Installation for Exploring the Neural Semantics of Image Synthesis

David Bau, Jaden Fiotto-Kaufman, Imke Grabe, Tom L. Jenkins
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Image Retrieval and Classification Techniques
article

Hidden Layers: An Interactive Installation for Exploring the Neural Semantics of Image Synthesis

David Bau, Jaden Fiotto-Kaufman, Imke Grabe, Tom L. Jenkins
article en

Abstract

Figure 1: A visualization of the hidden layers of our GAN-based prototype generating fashion imagery.Normally concealed within the black box of a generative model, this visualization reveals the activation of the hidden layers-progressing from left to right-consisting of many channels, here visualized as grids of neurons.Magenta pixels indicate positive, while cyan pixels represent negative activation of a neuron.We explore their material properties as a new modality for interaction.

Northeastern University (US), IT University of Copenhagen (DK)
Openalex Percentile: Top 78%
Image Retrieval and Classification Techniques
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