论文《Fashion Landmark Detection in the Wild》摘要:
Visual fashion analysis has attracted many attentions in the recent years.
Previous work represented clothing regions by either bounding boxes or human
joints. This work presents fashion landmark detection or fashion alignment,
which is to predict the positions of functional key points defined on the
fashion items, such as the corners of neckline, hemline, and cuff. To encourage
future studies, we introduce a fashion landmark dataset with over 120K images,
where each image is labeled with eight landmarks. With this dataset, we study
fashion alignment by cascading multiple convolutional neural networks in three
stages. These stages gradually improve the accuracies of landmark predictions.
Extensive experiments demonstrate the effectiveness of the proposed method, as
well as its generalization ability to pose estimation. Fashion landmark is also
compared to clothing bounding boxes and human joints in two applications,
fashion attribute prediction and clothes retrieval, showing that fashion
landmark is a more discriminative representation to understand fashion images.
论文原文、代码和数据集点击“阅读原文”即可下载。
项目主页:
http://personal.ie.cuhk.edu.hk/~lz013/projects/FashionLandmarks.html
原文链接:
http://weibo.com/1402400261/EwcKQBw9w?from=page_1005051402400261_profile&wvr=6&mod=weibotime&type=comment#_rnd1487500866679