# Form Forge: Latent Space Exploration of Architectural Forms via Explicit Latent Variable Manipulation

arXiv: https://arxiv.org/abs/2407.05079 · HTML: https://mlsanity.com/paper/2407.05079/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 14 references that are in the map.
- First posted on arXiv 6 Jul 2024.

## Builds on (most cited first, 6 of 6)

- [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018)
- [Rethinking the Inception Architecture for Computer Vision](https://mlsanity.com/paper/1512.00567/) (2015)
- [Training Generative Adversarial Networks with Limited Data](https://mlsanity.com/paper/2006.06676/) (2020)
- [GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation](https://mlsanity.com/paper/1809.01587/) (2018)
- [An HCI-Centric Survey and Taxonomy of Human-Generative-AI Interactions](https://mlsanity.com/paper/2310.07127/) (2023)
- [Latent Lab: Large Language Models for Knowledge Exploration](https://mlsanity.com/paper/2311.13051/) (2023)

## Abstract (arXiv)

This paper presents 'Form Forge,' a prototype of a creative system for interactively exploring the latent space of architectural forms, inspired by Franois Blanciak's SITELESS: 1001 Building Forms via direct manipulation of latent variables. Utilizing a fine-tuned StyleGAN2-ADA model, the system allows users to navigate an array of possible building forms derived from Blanciak's sketches. Distinct from common latent space exploration tools that often rely on projected navigation landmarks, Form Forge provides direct access to manipulate each latent variable, aiming to offer a more granular exploration of the model's capabilities. Form Forge's design is intended to simplify the interaction with a complex, high-dimensional space and to serve as a preliminary investigation into how such tools might support creative processes in architectural design.