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Reproducibility Companion Paper: Visual Relation of Interest Detection

Published: 17 October 2021 Publication History

Abstract

In 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 for conveying the main content of an image. In this paper, we explain the file structure of the source code and publish the details of our ViROI dataset, which can be used to retrain the model with custom parameters. We also detail the scripts for component analysis and comparison with other methods and list the parameters that can be modified for custom training and inference.

References

[1]
Xinpeng Chen, Lin Ma, Wenhao Jiang, Jian Yao, and Wei Liu. 2018. Regularizing rnns for caption generation by reconstructing the past with the present. In IEEE Conference on Computer Vision and Pattern Recognition. 7995--8003.
[2]
Marcella Cornia, Matteo Stefanini, Lorenzo Baraldi, and Rita Cucchiara. 2019. Mtextsuperscript2: Meshed-Memory Transformer for Image Captioning. arXiv preprint arXiv:1912.08226 (2019).
[3]
Qibin Hou, Ming-Ming Cheng, Xiaowei Hu, Ali Borji, Zhuowen Tu, and Philip HS Torr. 2017. Deeply supervised salient object detection with short connections. In IEEE Conference on Computer Vision and Pattern Recognition. 3203--3212.
[4]
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick. 2014. Microsoft coco: Common objects in context. In European Conference on Computer Vision. 740--755.
[5]
Cewu Lu, Ranjay Krishna, Michael Bernstein, and Li Fei-Fei. 2016. Visual relationship detection with language priors. In European Conference on Computer Vision. 852--869.
[6]
Zhiming Luo, Akshaya Mishra, Andrew Achkar, Justin A Eichel, Shaozi Li, and Pierremarc Jodoin. 2017. Non-local Deep Features for Salient Object Detection. In IEEE Conference on Computer Vision and Pattern Recognition .
[7]
Christopher D Manning, Mihai Surdeanu, John Bauer, Jenny Rose Finkel, Steven Bethard, and David McClosky. 2014. The Stanford CoreNLP natural language processing toolkit. In Association for Computational Linguistics System Demonstrations. 55--60.
[8]
Moshiko Raboh, Roei Herzig, Jonathan Berant, Gal Chechik, and Amir Globerson. 2020. Differentiable scene graphs. In IEEE Winter Conference on Applications of Computer Vision. 1488--1497.
[9]
Kaihua Tang, Hanwang Zhang, Baoyuan Wu, Wenhan Luo, and Wei Liu. 2019. Learning to compose dynamic tree structures for visual contexts. In IEEE Conference on Computer Vision and Pattern Recognition. 6619--6628.
[10]
Yuxin Wu, Alexander Kirillov, Francisco Massa, Wan-Yen Lo, and Ross Girshick. 2019. Detectron2. https://github.com/facebookresearch/detectron2.
[11]
Danfei Xu, Yuke Zhu, Christopher B Choy, and Li Fei-Fei. 2017. Scene graph generation by iterative message passing. In IEEE Conference on Computer Vision and Pattern Recognition. 5410--5419.
[12]
Jianwei Yang, Jiasen Lu, Stefan Lee, Dhruv Batra, and Devi Parikh. 2018a. Graph R-CNN for scene graph generation. In European Conference on Computer Vision. 670--685.
[13]
Xu Yang, Hanwang Zhang, and Jianfei Cai. 2018b. Shuffle-then-assemble: Learning object-agnostic visual relationship features. In European Conference on Computer Vision. 36--52.
[14]
Fan Yu, Haonan Wang, Tongwei Ren, Jinhui Tang, and Gangshan Wu. 2019. Instance of Interest Detection. In ACM International Conference on Multimedia.
[15]
Fan Yu, Haonan Wang, Tongwei Ren, Jinhui Tang, and Gangshan Wu. 2020. Visual Relation of Interest Detection. In ACM International Conference on Multimedia.
[16]
Rowan Zellers, Mark Yatskar, Sam Thomson, and Yejin Choi. 2018. Neural motifs: Scene graph parsing with global context. In IEEE Conference on Computer Vision and Pattern Recognition. 5831--5840.
[17]
Yibing Zhan, Jun Yu, Ting Yu, and Dacheng Tao. 2019. On Exploring Undetermined Relationships for Visual Relationship Detection. In IEEE Conference on Computer Vision and Pattern Recognition. 5128--5137.

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  1. Reproducibility Companion Paper: Visual Relation of Interest Detection

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    cover image ACM Conferences
    MM '21: Proceedings of the 29th ACM International Conference on Multimedia
    October 2021
    5796 pages
    ISBN:9781450386517
    DOI:10.1145/3474085
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 17 October 2021

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    1. interest estimation
    2. interest propagation network
    3. visual relation detection
    4. visual relation of interest

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    MM '21
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    MM '21: ACM Multimedia Conference
    October 20 - 24, 2021
    Virtual Event, China

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    Overall Acceptance Rate 995 of 4,171 submissions, 24%

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    MM '24
    The 32nd ACM International Conference on Multimedia
    October 28 - November 1, 2024
    Melbourne , VIC , Australia

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