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Tstars-Tryon 1.0:面向多样化时尚单品的鲁棒且逼真的虚拟试穿系统

Tstars-Tryon 1.0: Robust and Realistic Virtual Try-On for Diverse Fashion Items

April 21, 2026
作者: Mengting Chen, Zhengrui Chen, Yongchao Du, Zuan Gao, Taihang Hu, Jinsong Lan, Chao Lin, Yefeng Shen, Xingjian Wang, Zhao Wang, Zhengtao Wu, Xiaoli Xu, Zhengze Xu, Hao Yan, Mingzhou Zhang, Jun Zheng, Qinye Zhou, Xiaoyong Zhu, Bo Zheng
cs.AI

摘要

近期图像生成与编辑技术的突破为虚拟试穿开辟了新机遇,但现有方法仍难以满足复杂的现实需求。我们推出Tstars-Tryon 1.0——一个具备鲁棒性、真实感、多功能性及高商用效能的虚拟试穿系统。首先,该系统在极端姿态、强烈光照变化、运动模糊等复杂场景下仍保持高成功率;其次,生成结果具有照片级真实感,能精细保留服装纹理、材质属性与结构特征,并显著规避常见AI生成伪影;第三,除服装试穿外,模型支持8大时尚品类、最多6张参考图的灵活多图组合,并实现人物身份与背景的协同控制;第四,通过深度推理优化突破商用延迟瓶颈,实现近乎实时的生成体验。这些能力得益于端到端模型架构、可扩展数据引擎、鲁棒基础设施与多阶段训练范式的系统化整合。大规模评估及产品部署表明,Tstars-Tryon 1.0在整体性能上处于领先地位。为促进后续研究,我们同步发布了完整评估基准。该模型已在淘宝APP实现工业级部署,为数百万用户处理上千万次请求。
English
Recent advances in image generation and editing have opened new opportunities for virtual try-on. However, existing methods still struggle to meet complex real-world demands. We present Tstars-Tryon 1.0, a commercial-scale virtual try-on system that is robust, realistic, versatile, and highly efficient. First, our system maintains a high success rate across challenging cases like extreme poses, severe illumination variations, motion blur, and other in-the-wild conditions. Second, it delivers highly photorealistic results with fine-grained details, faithfully preserving garment texture, material properties, and structural characteristics, while largely avoiding common AI-generated artifacts. Third, beyond apparel try-on, our model supports flexible multi-image composition (up to 6 reference images) across 8 fashion categories, with coordinated control over person identity and background. Fourth, to overcome the latency bottlenecks of commercial deployment, our system is heavily optimized for inference speed, delivering near real-time generation for a seamless user experience. These capabilities are enabled by an integrated system design spanning end-to-end model architecture, a scalable data engine, robust infrastructure, and a multi-stage training paradigm. Extensive evaluation and large-scale product deployment demonstrate that Tstars-Tryon1.0 achieves leading overall performance. To support future research, we also release a comprehensive benchmark. The model has been deployed at an industrial scale on the Taobao App, serving millions of users with tens of millions of requests.
PDF796April 23, 2026