论文标题
现实世界衣服检索系统的有效管道
An Effective Pipeline for a Real-world Clothes Retrieval System
论文作者
论文摘要
在本文中，我们提出了一条有效的服装检索系统管道，该系统对大型现实世界时尚数据具有坚固性。我们提出的方法包括三个组成部分：检测，检索和后处理。首先，我们执行检测任务，以精确检索目标衣服，然后使用基于公制的学习模型检索相应的项目。为了提高针对噪声和误导性边界框的检索鲁棒性，我们采用了后处理方法，例如加权框融合和功能串联。借助拟议的方法，我们在2020年DeepFashion2服装检索挑战中获得了第二名。
In this paper, we propose an effective pipeline for clothes retrieval system which has sturdiness on large-scale real-world fashion data. Our proposed method consists of three components: detection, retrieval, and post-processing. We firstly conduct a detection task for precise retrieval on target clothes, then retrieve the corresponding items with the metric learning-based model. To improve the retrieval robustness against noise and misleading bounding boxes, we apply post-processing methods such as weighted boxes fusion and feature concatenation. With the proposed methodology, we achieved 2nd place in the DeepFashion2 Clothes Retrieval 2020 challenge.
