Tstars-Tryon 1.0:實現多元時尚單品的強健逼真虛擬試穿
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
近期圖像生成與編輯技術的突破為虛擬試穿開闢了新可能,但現有方法仍難以滿足複雜的實際應用需求。我們推出商用級虛擬試穿系統Tstars-Tryon 1.0,該系統具備強韌性、真實性、多功能性與高效能四大特點。首先,系統在極端姿勢、劇烈光照變化、動態模糊等複雜真實場景下仍保持高成功率;其次,生成結果具有照片級真實感,能精細還原服裝紋理、材質屬性與結構特徵,同時有效規避常見的AI生成瑕疵;第三,除常規服飾試穿外,模型支援8大時尚品類的靈活多圖組合(最多6張參考圖),並可協調控制人物身份與背景元素;第四,針對商業部署的延遲瓶頸,系統進行深度推理優化,實現近乎即時的生成速度以保障用戶體驗。這些能力得益於端到端模型架構、可擴展數據引擎、穩健基礎設施與多階段訓練範式的系統化設計。大量評估與大規模產品部署表明,Tstars-Tryon 1.0在整體性能上處於領先地位。為推動後續研究,我們同步發布了綜合評估基準。該模型已在淘寶App實現工業化部署,日均服務數百萬用戶,處理千萬級請求。
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.