DesignFromX: Empowering Consumer-Driven Design Space Exploration through Feature Composition of Referenced Products
Runlin Duan, Chenfei Zhu, Yuzhao Chen, Yichen Hu, Jingyu Shi, Karthik Ramani

TL;DR
DesignFromX leverages generative AI to enable consumers to explore and design new products by composing features from reference images, making the process more engaging and accessible.
Contribution
The paper introduces a novel system that helps consumers identify and compose product features using AI, facilitating consumer-driven design exploration.
Findings
Participants found the system easy to use and engaging.
The system reduced frustration in design exploration.
Participants successfully generated new product concepts.
Abstract
Industrial products are designed to satisfy the needs of consumers. The rise of generative artificial intelligence (GenAI) enables consumers to easily modify a product by prompting a generative model, opening up opportunities to incorporate consumers in exploring the product design space. However, consumers often struggle to articulate their preferred product features due to their unfamiliarity with terminology and their limited understanding of the structure of product features. We present DesignFromX, a system that empowers consumer-driven design space exploration by helping consumers to design a product based on their preferences. Leveraging an effective GenAI-based framework, the system allows users to easily identify design features from product images and compose those features to generate conceptual images and 3D models of a new product. A user study with 24 participants…
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