Virtual try-on(VTON) aims at fitting target clothes to reference person images, which is widely adopted in e-commerce.Existing VTON approaches can be narrowly categorized into Parser-Based(PB) and Parser-Free(PF) by whether relying on the parser information to mask the persons' clothes and synthesize try-on images. Although abandoning parser information has improved the applicability of PF methods, the ability of detail synthesizing has also been sacrificed. As a result, the distraction from original cloth may persistin synthesized images, especially in complicated postures and high resolution applications. To address the aforementioned issue, we propose a novel PF method named Regional Mask Guided Network(RMGN). More specifically, a regional mask is proposed to explicitly fuse the features of target clothes and reference persons so that the persisted distraction can be eliminated. A posture awareness loss and a multi-level feature extractor are further proposed to handle the complicated postures and synthesize high resolution images. Extensive experiments demonstrate that our proposed RMGN outperforms both state-of-the-art PB and PF methods.Ablation studies further verify the effectiveness ofmodules in RMGN.

提出了一种新的基于区域遮罩引导网络的虚拟试穿方法，该方法通过引入区域遮罩，显式地融合目标服饰和参考人物的特征以消除详细合成中存在的干扰，并通过姿势感知损失和多级特征提取器进一步处理复杂的姿势和高分辨率图像合成。大量实验表明，所提出的方法优于现有方法，验证了RMGN中的模块的有效性。

RMGN:基于区域掩码的网络，用于无需解析的虚拟试衣