Attribute driven zero-shot classification and segmentation

Shu Yang, Yemin Shi, Yaowei Wang*, Jing Wang, Zesong Fei

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

3 引用 (Scopus)

摘要

Zero-shot classification and segmentation aims to recognize and segment objects of unseen classes. The attribute information, such as color, shape, part and material, is usually used for zero-shot classification. Moreover, we observe that this kind of attribute information could also be helpful in the segmentation task. On this basis, we propose an Attribute-Segmentation-Attribute (ASA) framework to address the zero-shot classification and segmentation problem. In the framework, a multi-task model is pre-trained to capture category and attribute features simultaneously. Then, a two-branch fully convolutional structure is built on the pre-trained model and fine-tuned for segmentation task. Finally, the extracted class-unseen object is recognized with the segmentation-assisted attribute prediction and a class-attribute matrix. Experimental results on the public bench-mark datasets indicate that the proposed ASA framework out-performs the state-of-the-art methods for both classification and segmentation tasks.

源语言英语
主期刊名2018 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2018
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9781538641958
DOI
出版状态已出版 - 28 11月 2018
活动2018 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2018 - San Diego, 美国
期限: 23 7月 201827 7月 2018

出版系列

姓名2018 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2018

会议

会议2018 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2018
国家/地区美国
San Diego
时期23/07/1827/07/18

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引用此

Yang, S., Shi, Y., Wang, Y., Wang, J., & Fei, Z. (2018). Attribute driven zero-shot classification and segmentation. 在 2018 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2018 文章 8551489 (2018 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMEW.2018.8551489