Reproducibility Companion Paper: Instance of Interest Detection
Authors: 
Fan Yu, Dandan Wang, Haonan Wang, Tongwei Ren, Jinhui Tang, Gangshan Wu, Jingjing Chen, 
Michael RieglerAuthors Info & Claims
Fan Yu, Dandan Wang, Haonan Wang, Tongwei Ren, Jinhui Tang, Gangshan Wu, Jingjing Chen, Michael RieglerAuthors Info & ClaimsPages 4435 - 4438
Abstract
To support the replication of "Instance of Interest Detection", which was presented at MM'19, this companion paper provides the details of the artifacts. Instance of Interest Detection (IOID) aims to provide instance-level user interest modeling for image semantic description. In this paper, we explain the file structure of the source code and publish the details of our IOID dataset, which can be used to retrain the model with custom parameters. We also provide a program for component analysis to help other researchers to do experiments with alternative models that are not included in our experiments. Moreover, we provide a demo program for using our model easily.
Supplementary Material
To support the replication of ?Instance of Interest Detection?, which was presented at MM?19, this companion paper provides the details of the artifacts. Instance of Interest Detection aims to provide instance-level user interest modeling for image semantic description. In this paper, we explain the file structure of the source code and publish the details of our IOID dataset, which can be used to retrain the model with custom parameters. We also provide a program for component analysis to help other researchers to do experiments with alternative models that are not included in our experiments. Moreover, we provide a demo program for using our model easily.
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References
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Liangchieh Chen, George Papandreou, Iasonas Kokkinos, Kevin P Murphy, and Alan L Yuille. 2018. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets and Atrous Convolution and and Fully Connected CRFs. IEEE Transactions on Pattern Analysis and Machine Intelligence (2018), 843--848.
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Kaiming He, Georgia Gkioxari, Piotr Dollar, and Ross B Girshick. 2017. Mask R-CNN. IEEE Conference on Computer Vision and Pattern Recognition.
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Qibin Hou, Mingming Cheng, Xiaowei Hu, Ali Borji, Zhuowen Tu, and Philip H S Torr. 2017. Deeply Supervised Salient Object Detection with Short Connections. IEEE Conference on Computer Vision and Pattern Recognition.
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Guanbin Li, Yuan Xie, Liang Lin, and Yizhou Yu. 2017. Instance-Level Salient Object Segmentation. In IEEE Conference on Computer Vision and Pattern Recognition .
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Nian Liu, Junwei Han, and Minghsuan Yang. 2018. PiCANet: Learning Pixel-Wise Contextual Attention for Saliency Detection. IEEE Conference on Computer Vision and Pattern Recognition.
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Zhiming Luo, Akshaya Kumar Mishra, Andrew Achkar, Justin A Eichel, Shaozi Li, and Pierremarc Jodoin. 2017. Non-local Deep Features for Salient Object Detection. IEEE Conference on Computer Vision and Pattern Recognition.
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Fan Yu, Haonan Wang, Tongwei Ren, Jinhui Tang, and Gangshan Wu. 2019. Instance of Interest Detection. ACM International Conference on Multimedia.
Index Terms
- Reproducibility Companion Paper: Instance of Interest Detection
Recommendations
Instance of Interest Detection
MM '19: Proceedings of the 27th ACM International Conference on MultimediaIn this paper, we propose a novel task named Instance of Interest Detection (IOID) to provide instance-level user interest modeling for image semantic description. IOID focuses on extracting the instances which are beneficial to represent image content, ...
Reproducibility Companion Paper: Visual Relation of Interest Detection
MM '21: Proceedings of the 29th ACM International Conference on MultimediaIn this companion paper, we provide the details of the reproducibility artifacts of the paper "Visual Relation of Interest Detection" presented at MM'20. Visual Relation of Interest Detection (VROID) aims to detect visual relations that are important ...
Visual Relation of Interest Detection
MM '20: Proceedings of the 28th ACM International Conference on MultimediaIn this paper, we propose a novel Visual Relation of Interest Detection (VROID) task, which aims to detect visual relations that are important for conveying the main content of an image, motivated from the intuition that not all correctly detected ...
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Information & Contributors
Information
Published In
October 2020
4889 pages
ISBN:9781450379885
DOI:10.1145/3394171
- General Chairs:
- Chang Wen Chen,
- Rita Cucchiara,
- Xian-Sheng Hua,
- Program Chairs:
- Guo-Jun Qi,
- Elisa Ricci,
- Zhengyou Zhang,
- Roger Zimmermann
Copyright © 2020 ACM.
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Published: 12 October 2020
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- Science,Technology and Innovation Commission of Shenzhen Municipality
- Collaborative Innovation Center of Novel Software Technology and Industrialization
- Natural Science Foundation of Jiangsu Province
- National Science Foundation of China
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MM '20
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