AI Assisted Apparel Design
Alpana Dubey, Nitish Bhardwaj, Kumar Abhinav, Suma Mani Kuriakose,, Sakshi Jain, Veenu Arora

TL;DR
This paper introduces AI-powered tools to assist apparel designers by generating new clothing designs through style merging and transfer, aiming to streamline design creation and enhance creativity.
Contribution
It presents two novel AI assistants for apparel design, along with a new dataset with detailed apparel component annotations, improving design generation and analysis.
Findings
Generated designs are of high quality and suitable for fabrication.
Designers reported increased creativity and efficiency using the system.
The system effectively analyzes trending apparel attributes.
Abstract
Fashion is a fast-changing industry where designs are refreshed at large scale every season. Moreover, it faces huge challenge of unsold inventory as not all designs appeal to customers. This puts designers under significant pressure. Firstly, they need to create innumerous fresh designs. Secondly, they need to create designs that appeal to customers. Although we see advancements in approaches to help designers analyzing consumers, often such insights are too many. Creating all possible designs with those insights is time consuming. In this paper, we propose a system of AI assistants that assists designers in their design journey. The proposed system assists designers in analyzing different selling/trending attributes of apparels. We propose two design generation assistants namely Apparel-Style-Merge and Apparel-Style-Transfer. Apparel-Style-Merge generates new designs by combining high…
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Taxonomy
TopicsGenerative Adversarial Networks and Image Synthesis · Image Processing and 3D Reconstruction · Manufacturing Process and Optimization
