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

Year: 2019

Type: article

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].

Source: ACM Transactions on Multimedia Computing Communications and Applications

DOI: 10.1145/3292061

Authors: Xavier Alameda-Pineda, Miriam Redi, Mohammad Soleymani, Nicu Sebe, Shih-Fu Chang, Samuel Gosling

Institutions: Institut national de recherche en sciences et technologies du numérique, King's College London, University of Geneva, University of Trento, Columbia University, The University of Texas at Austin

Language: English

Topic: Image and Video Quality Assessment

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2914421969

FWCI: 0.112

Cites: 10

Cited by: 1

Related to: 10