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FacesMM - 2018 : Faces in Multimedia in conjunction with 2018 ICME | |||||||||||||||
Link: https://web.northeastern.edu/smilelab/FacesMM2018/index.html | |||||||||||||||
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Call For Papers | |||||||||||||||
CALL FOR PAPERS
Faces in Multimedia Workshop calls for novel work in the automatic understanding of faces. As a Workshop held in conjunction with the 2018 IEEE International Conference on Multimedia and Expo (ICME 2018), we are looking for work from different views (i.e., various types of data) and multi-modal approaches (i.e., multimedia). We are looking for quality papers (long and short) that spans various faces-related problems. Special attention will be given to work on kinship. Thus, this provides a platform for novel work, state-of-the-art methodologies, nature-based studies, innovative ideas concerning kinship. With the minds and efforts of the research communities, we to both integrate kin-related work across domains/ fields and push the frontier of automatic face recognition technologies and, ultimately, bridge the gap between research-and-reality. More information about Faces in Multimedia Workshop can be found here, https://web.northeastern.edu/smilelab/FacesMM2018/index.html For more information about ICME 2018 check out http://www.icme2018.org/. The best paper award will be awarded. TOPIC SUGGESTIONS This workshop serves a forum for researchers to review the recent progress of recognition, analysis, and modeling of faces in multimedia. Special interests will be given to visual kin and non-kin social relations. The workshop will include up to two keynotes, along with peer-reviewed papers (oral and poster). Original high-quality contributions are solicited on the following topics: -- Soft biometrics and profiling of faces: age, gender, ethnicity, personality, kinship, occupation, and beauty ranking; -- Deep learning practice for social face problems with ambiguity including kinship verification, family recognition, and retrieval; -- Understanding of the familial features from vast amount of social media data; -- Discovery of the social groups from faces and the context; -- Mining social face relations through metadata as well as visual information; -- Tracking and extraction and analysis of face models captured by mobile devices; -- Face recognition in low-quality or low-resolution video or images; -- Novel mathematical models and algorithms, sensors and modalities for face & body gesture and action representation; -- Analysis and recognition for cross-domain social media; -- Novel social applications involving detection, tracking & recognition of faces; -- Face analysis for sentiment analysis in social media; -- Other applications involving face analysis in social media content. |
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