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Special Section on Multimodal Understanding of Social, Affective, and Subjective Attributes

Authors
Alameda-Pineda, Xavier
Redi, Miriam
Sebe, Nicu
Chang, Shih-Fu
Gosling, Samuel
Published in ACM Transactions on Multimedia Computing, Communications, and Applications. 2019, vol. 15, no. 11, p. 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].
Keywords Subjective attributesMultimodal data
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ALAMEDA-PINEDA, Xavier et al. Special Section on Multimodal Understanding of Social, Affective, and Subjective Attributes. In: ACM Transactions on Multimedia Computing, Communications, and Applications, 2019, vol. 15, n° 11, p. 1-3. https://archive-ouverte.unige.ch/unige:119712

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Deposited on : 2019-06-19

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