CoStitch: Disentangled Color Style and Stitch Texture Generation for Controllable Embroidery Synthesis

Embroidery image synthesis aims to generate realistic embroidery images with specified color styles and stitch textures while preserving target pattern structure. However, existing methods typically encode color style and stitch texture within a unified appearance representation, hindering their disentanglement and independent reuse on novel patterns. To address this issue, we propose CoStitch, a framework for disentangled color style and stitch texture generation. CoStitch exploits three progressively enriched image states to provide differentiated supervision for the two attributes. Specifically, CoStitch constructs an aligned triplet comprising a sketch, a color design image, and an embroidery image, where the color design image serves as an intermediate state that distinguishes color-related variation from stitch-texture variation. CoStitch further performs joint image-text response analysis to identify color-sensitive and texture-sensitive blocks, defining attribute-specific learning subsets for Color LoRA and Stitch LoRA to reduce cross-attribute interference. The three image states are then reconstructed successively with corresponding LoRA updates, progressively learning color style and fine-grained stitch texture. Finally, texture enhancement stops sketch reconstruction and further refines stitch direction, length, density, and arrangement while preserving the learned color style. Experiments demonstrate that CoStitch preserves target pattern structure while enabling color style and stitch texture to be reused independently and flexibly combined across different references.