Style-Instructed Mask-Free Virtual Try On

Fuente: arXiv
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Hauptverfasser: Zhang, Mengqi, Li, Qi, Seyfioglu, Mehmet Saygin, Bouyarmane, Karim
Format: Preprint
Veröffentlicht: 2026
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author Zhang, Mengqi
Li, Qi
Seyfioglu, Mehmet Saygin
Bouyarmane, Karim
author_facet Zhang, Mengqi
Li, Qi
Seyfioglu, Mehmet Saygin
Bouyarmane, Karim
contents Virtual Try-On is a promising research area with broad applications in e-commerce and everyday life, enabling users to visualize garments on themselves or others before purchase. Most existing methods depend on predefined or user-specified masks to guide garment placement, but their performance is highly sensitive to mask quality, often causing misalignment or artifacts, and introduces redundant steps for users. To overcome these limitations, we propose a mask-free virtual try-on framework that requires only minimal modifications to the underlying architecture while remaining compatible with common diffusion-based pipelines. To address the increased ambiguity in the absence of masks, we integrate an attention-based guidance mechanism that explicitly directs the model to focus on the target garment region and improves correspondence between the garment and the person. Additionally, we incorporate instruction prompts, allowing users to flexibly control garment categories and wearing styles, addressing the underutilization of prompts in prior work and improving interaction flexibility. Both qualitative and quantitative evaluations across multiple datasets demonstrate that our approach consistently outperforms existing methods, producing more accurate, robust, and user-friendly try-on results.
format Preprint
id arxiv_https___arxiv_org_abs_2603_29587
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Style-Instructed Mask-Free Virtual Try On
Zhang, Mengqi
Li, Qi
Seyfioglu, Mehmet Saygin
Bouyarmane, Karim
Graphics
Virtual Try-On is a promising research area with broad applications in e-commerce and everyday life, enabling users to visualize garments on themselves or others before purchase. Most existing methods depend on predefined or user-specified masks to guide garment placement, but their performance is highly sensitive to mask quality, often causing misalignment or artifacts, and introduces redundant steps for users. To overcome these limitations, we propose a mask-free virtual try-on framework that requires only minimal modifications to the underlying architecture while remaining compatible with common diffusion-based pipelines. To address the increased ambiguity in the absence of masks, we integrate an attention-based guidance mechanism that explicitly directs the model to focus on the target garment region and improves correspondence between the garment and the person. Additionally, we incorporate instruction prompts, allowing users to flexibly control garment categories and wearing styles, addressing the underutilization of prompts in prior work and improving interaction flexibility. Both qualitative and quantitative evaluations across multiple datasets demonstrate that our approach consistently outperforms existing methods, producing more accurate, robust, and user-friendly try-on results.
title Style-Instructed Mask-Free Virtual Try On
topic Graphics
url https://arxiv.org/abs/2603.29587