Core Concepts
HAIFIT introduces a novel approach to transform sketches into high-fidelity clothing images, excelling in preserving intricate details essential for fashion design applications.
Abstract
I. Abstract:
Sketches are crucial in expressing an artist's vision in fashion design.
Existing methods compromise sketch details during image generation.
II. Introduction:
Sketches evolve through iterative refinement in the design process.
A robust sketch-to-image method aids designers in previewing and refining sketches.
III. Methodology:
HAIFIT integrates Multi-scale Feature Fusion Encoder (MFFE) and Cross-level Skip Connection (CSC).
MFFE captures global contour features and abstract intent features from sketches.
CSC enhances the quality of generated images by incorporating feature correlations across different layers.
IV. Experiments:
HAIFashion dataset includes 933 sketch-image pairs hand-drawn by professional designers.
HAIFIT outperforms state-of-the-art approaches in generating realistic clothing images.
V. Conclusion:
HAIFIT effectively generates high-quality clothing images while maintaining the design style of sketches.
Stats
HAIFITは、ファッションデザインにおけるスケッチを高忠実度の衣料品画像に変換する革新的なアプローチを紹介します。