ClothFormer:Taming Video Virtual Try-on in All Module
Jianbin Jiang, Tan Wang, He Yan, Junhui Liu

TL;DR
ClothFormer is a novel framework for video virtual try-on that achieves realistic, harmonious, and temporally consistent results by addressing occlusion, background complexity, and motion smoothing through specialized modules.
Contribution
The paper introduces ClothFormer, a comprehensive video try-on system with three key modules for occlusion handling, flow smoothing, and texture fusion, advancing the state-of-the-art in video virtual try-on.
Findings
Outperforms baselines in video quality metrics
Produces more realistic and consistent try-on videos
Effectively handles occlusions and complex backgrounds
Abstract
The task of video virtual try-on aims to fit the target clothes to a person in the video with spatio-temporal consistency. Despite tremendous progress of image virtual try-on, they lead to inconsistency between frames when applied to videos. Limited work also explored the task of video-based virtual try-on but failed to produce visually pleasing and temporally coherent results. Moreover, there are two other key challenges: 1) how to generate accurate warping when occlusions appear in the clothing region; 2) how to generate clothes and non-target body parts (e.g. arms, neck) in harmony with the complicated background; To address them, we propose a novel video virtual try-on framework, ClothFormer, which successfully synthesizes realistic, harmonious, and spatio-temporal consistent results in complicated environment. In particular, ClothFormer involves three major modules. First, a…
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Taxonomy
TopicsAdvanced Vision and Imaging · Generative Adversarial Networks and Image Synthesis · 3D Shape Modeling and Analysis
