DeepFashion 服饰数据集

这是一个具有全面标注的大型服饰数据集。基于此数据集开发的四个 benchmark 分别是 Attribute Prediction 、 Consumer-to-shop Clothes Retrieval 、 In-shop Clothes Retrieval and Landmark Detection 。这些基准的数据和标注可用作计算机视觉任务的训练集和测试集，比如服饰检测、服饰识别、图像检索等。

This is a large-scale clothing dataset with comprehensive annotations. Four benchmarks developed based on this dataset are Attribute Prediction, Consumer-to-shop Clothes Retrieval, In-shop Clothes Retrieval, and Landmark Detection respectively. The data and annotations of these benchmarks can serve as training and test sets for computer vision tasks, such as clothing detection, clothing recognition, image retrieval, and so on.

搜集汇总

背景与挑战

背景概述

DeepFashion是一个大型服饰数据集，包含80万张服饰图片，涵盖50个类别和1,000个描述属性，适用于服饰检测、识别和图像检索等计算机视觉任务。数据集还提供四个基准测试，包括属性预测、消费者到商店的服装检索、店内服装检索和地标检测。