# Tstars-Tryon 1.0：面向多样化时尚单品的稳健逼真虚拟试衣系统

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-04-21 08:00
- AIHOT 链接：https://aihot.virxact.com/items/cmo9f1psx023vsls2r15bpnsc
- 原文链接：https://arxiv.org/abs/2604.19748

## AI 摘要

Tstars-Tryon 1.0 是一款商业级虚拟试衣系统，能够在极端姿势、光照变化和动态模糊等复杂场景下保持高成功率，生成保留服装纹理与材质细节的高保真图像。系统支持多达6张参考图的多图合成，覆盖8个时尚品类，并针对推理速度进行优化实现近实时生成。该技术已在淘宝App大规模部署，服务数百万用户并处理数千万次请求，同时团队发布了综合基准数据集以支持后续研究。

## 正文

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.