ChatGarment: Garment Estimation, Generation and Editing via Large Language Models
project arXiv video code data
We introduce ChatGarment, a novel approach that leverages large vision-language models (VLMs) to automate the estimation, generation, and editing of 3D garment sewing patterns from images or text descriptions. Unlike previous methods that often lack robustness and interactive editing capabilities, ChatGarment finetunes a VLM to produce GarmentCode, a JSON-based, language-friendly format for 2D sewing patterns, enabling both estimating and editing from images and text instructions. To optimize performance, we refine GarmentCode by expanding its support for more diverse garment types and simplifying its structure, making it more efficient for VLM finetuning. Additionally, we develop an automated data construction pipeline to generate a large-scale dataset of image-to-sewing-pattern and text-to-sewing-pattern pairs, empowering ChatGarment with strong generalization across various garment types. Extensive evaluations demonstrate ChatGarment’s ability to accurately reconstruct, generate, and edit garments from multimodal inputs, highlighting its potential to revolutionize workflows in fashion and gaming applications.
| Author(s): | Siyuan Bian and Chenghao Xu and Yuliang Xiu and Artur Grigorev and Zhen Liu and Cewu Lu and Michael J. Black and Yao Feng |
| Links: | |
| Book Title: | IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR) |
| Year: | 2025 |
| Month: | June |
| Day: | 11 |
| Bibtex Type: | Conference Paper (inproceedings) |
| Event Place: | Nashville, TN |
| State: | Published |
BibTex
@inproceedings{ChatGarment2025,
title = {{ChatGarment}: Garment Estimation, Generation and Editing via Large Language Models},
booktitle = {IEEE/CVF Conf.~on Computer Vision and Pattern Recognition (CVPR)},
abstract = {We introduce ChatGarment, a novel approach that leverages large vision-language models (VLMs) to automate the estimation, generation, and editing of 3D garment sewing patterns from images or text descriptions. Unlike previous methods that often lack robustness and interactive editing capabilities, ChatGarment finetunes a VLM to produce GarmentCode, a JSON-based, language-friendly format for 2D sewing patterns, enabling both estimating and editing from images and text instructions. To optimize performance, we refine GarmentCode by expanding its support for more diverse garment types and simplifying its structure, making it more efficient for VLM finetuning. Additionally, we develop an automated data construction pipeline to generate a large-scale dataset of image-to-sewing-pattern and text-to-sewing-pattern pairs, empowering ChatGarment with strong generalization across various garment types. Extensive evaluations demonstrate ChatGarment’s ability to accurately reconstruct, generate, and edit garments from multimodal inputs, highlighting its potential to revolutionize workflows in fashion and gaming applications.},
month = jun,
year = {2025},
slug = {chatgarment2025},
author = {Bian, Siyuan and Xu, Chenghao and Xiu, Yuliang and Grigorev, Artur and Liu, Zhen and Lu, Cewu and Black, Michael J. and Feng, Yao},
month_numeric = {6}
}