让虚拟试衣更贴合身体，支持自定义服装版型控制。
FitControler: Toward Fit-Aware Virtual Try-On
- 通过可学习模块实现服装版型的精准控制。
- 构建包含1.3万组数据的Fit4Men数据集，覆盖多种版型和姿势。
- 适用于各类试衣模型，提升服装贴合度与风格一致性。
真实感虚拟试衣不仅需精准还原服装细节，还需协调整体风格。现有方法多关注细节呈现，却忽视了影响整体风格的关键因素——服装版型。版型指服装与穿着者身体的贴合程度，是时尚设计的核心要素。本文提出面向版型感知的虚拟试衣（Fit-aware VTON），并设计可插拔的FitControler模块，支持在多种现代试衣模型中实现定制化版型控制。为解决版型布局生成与匹配渲染两大挑战，我们提出一个版型感知布局生成器，基于无服装先验的表征重绘人体-服装布局；再通过多尺度版型注入器将布局提示传递至试衣流程。同时构建名为Fit4Men的数据集，包含13,000对不同版型的上衣与下装组合，涵盖多视角、多姿态场景。引入两种版型一致性评估指标。大量实验表明，FitControler可兼容多种试衣模型，实现高精度版型调控。代码与数据将公开。
原文摘要 · Abstract (English)
Realistic virtual try-on (VTON) concerns not only faithful rendering of garment details but also coordination of the style. Prior art typically pursues the former, but neglects a key factor that shapes the holistic style -- garment fit. Garment fit delineates how a garment aligns with the body of a wearer and is a fundamental element in fashion design. In this work, we introduce fit-aware VTON and present FitControler, a learnable plug-in that can seamlessly integrate into modern VTON models to enable customized fit control. To achieve this, we highlight two challenges: i) how to delineate layouts of different fits and ii) how to render the garment that matches the layout. FitControler first features a fit-aware layout generator to redraw the body-garment layout conditioned on a set of delicately processed garment-agnostic representations, and a multi-scale fit injector is then used to deliver layout cues to enable layout-driven VTON. In particular, we build a fit-aware VTON dataset termed Fit4Men, including 13,000 body-garment pairs of different fits, covering both tops and bottoms, and featuring varying camera distances and body poses. Two fit consistency metrics are also introduced to assess the fitness of generations. Extensive experiments show that FitControler can work with various VTON models and achieve accurate fit control. Code and data will be released.
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