Fashion Landmark Detection in the Wild
Other conference paper

替代計量分析
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其它資訊
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.

出版社接受日期11.07.2016
著者Ziwei Liu, Sijie Yan, Ping Luo, Xiaogang Wang, Xiaoou Tang
會議名稱The 14th European Conference on Computer Vision
會議開始日08.10.2016
會議完結日16.10.2016
會議地點Amsterdam
會議國家/地區荷蘭
期刊名稱Lecture Notes in Artificial Intelligence
會議論文集題名Computer Vision – ECCV 2016
系列標題Lecture Notes in Computer Science
叢書冊次9906
出版年份2016
卷號9906
出版社Springer International Publishing
頁次229 - 245
國際標準書號978-3-319-46474-9
電子國際標準書號978-3-319-46475-6
國際標準期刊號0302-9743
語言美式英語

上次更新時間 2020-04-08 於 03:24