Special Section on Multimodal Understanding of Social, Affective, and Subjective Attributes
Authors: 
Xavier Alameda-Pineda, Miriam Redi, Mohammad Soleymani, Nicu Sebe, Shih-Fu Chang, Samuel GoslingAuthors Info & Claims
Xavier Alameda-Pineda, Miriam Redi, Mohammad Soleymani, Nicu Sebe, Shih-Fu Chang, Samuel GoslingAuthors Info & ClaimsArticle No.: 11, Pages 1 - 3
Abstract
Multimedia scientists have largely focused their research on the recognition of tangible properties of data such as objects and scenes. Recently, the field has started evolving toward the modeling of more complex properties. For example, the understanding of social, affective, and subjective attributes of visual data has attracted the attention of many research teams at the crossroads of computer vision, multimedia, and social sciences. These intangible attributes include, for example, visual beauty, video popularity, or user behavior. Multiple, diverse challenges arise when modeling such properties from multimedia data. The sections concern technical aspects such as reliable groundtruth collection, the effective learning of subjective properties, or the impact of context in subjective perception; see Refs. [2] and [3].
References
[1]
Xavier Alameda-Pineda, Andrea Pilzer, Dan Xu, Nicu Sebe, and Elisa Ricci. 2017. Viraliency: Pooling local viraliry. In IEEE CVPR.
[2]
Xavier Alameda-Pineda, Miriam Redi, Nicu Sebe, Shih-Fu Chang, and Jiebo Luo. 2018. ACM MM’18 workshop on understanding subjective attributes of data, multimodal recognition of evoked emotions. In ACM International Conference on Multimedia.
[3]
Xavier Alameda-Pineda, Miriam Redi, Mohammad Soleymani, Nicu Sebe, Shih-Fu Chang, and Samuel Gosling. 2017. MUSA2—First ACM workshop on multimodal understanding of social, affective and subjective attributes. In ACM Multimedia.
[4]
Xavier Alameda-Pineda, Elisa Ricci, Yan Yan, and Nicu Sebe. 2016. Recognizing emotions from abstract paintings using non-linear matrix completion. In IEEE CVPR.
[5]
Michael Gygli, Helmut Grabner, Hayko Riemenschneider, and Luc Van Gool. 2013. The interestingness of images. In ICCV.
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Brendan Jou, Tao Chen, Nikolaos Pappas, Miriam Redi, Mercan Topkara, and Shih-Fu Chang. 2015. Visual affect around the world: A large-scale multilingual visual sentiment ontology. In ACM International Conference on Multimedia.
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Aliaksandr Siarohin, Gloria Zen, Cveta Majtanovic, Xavier Alameda-Pineda, Elisa Ricci, and Nicu Sebe. 2017. How to make an image more memorable? A deep style transfer approach. In ACM ICMR.
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Index Terms
- Special Section on Multimodal Understanding of Social, Affective, and Subjective Attributes
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January 2019
265 pages
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Association for Computing Machinery
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Publication History
Published: 24 January 2019
Published in TOMM Volume 15, Issue 1s
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