Details
| Original language | English |
|---|---|
| Title of host publication | ICMR '24 |
| Subtitle of host publication | Proceedings of the 2024 International Conference on Multimedia Retrieval |
| Pages | 1342-1344 |
| Number of pages | 3 |
| ISBN (electronic) | 9798400706028 |
| Publication status | Published - 7 Jun 2024 |
| Event | 2024 International Conference on Multimedia Retrieval, ICMR 2024 - Phuket, Thailand Duration: 10 Jun 2024 → 14 Jun 2024 |
Abstract
Multimodal human understanding and analysis are emerging research areas that cut through several disciplines like Computer Vision (CV), Natural Language Processing (NLP), Speech Processing, Human-Computer Interaction (HCI), and Multimedia. Several multimodal learning techniques have recently shown the benefit of combining multiple modalities in image-text, audio-visual and video representation learning and various downstream multimodal tasks. At the core, these methods focus on modelling the modalities and their complex interactions by using large amounts of data, different loss functions and deep neural network architectures. However, for many Web and Social media applications, there is the need to model the human, including the understanding of human behaviour and perception. For this, it becomes important to consider interdisciplinary approaches, including social sciences and psychology. The core is understanding various cross-modal relations, quantifying bias such as social biases, and the applicability of models to real-world problems. Interdisciplinary theories such as semiotics or gestalt psychology can provide additional insights on perceptual understanding through signs and symbols across multiple modalities. In general, these theories provide a compelling view of multimodality and perception that can further expand computational research and multimedia applications on the Web and Social media. The theme of the MUWS workshop, multimodal human understanding, includes various interdisciplinary challenges related to social bias analyses, multimodal representation learning, detection of human impressions or sentiment, hate speech, sarcasm in multimodal data, multimodal rhetoric and semantics, and related topics. The MUWS workshop is an interactive event and includes keynotes by relevant experts, a poster session, research presentations and discussion.
Keywords
- human understanding, image-text relations, machine learning, multimodality, semiotics, social media, web
ASJC Scopus subject areas
- Computer Science(all)
- Computer Graphics and Computer-Aided Design
- Computer Science(all)
- Human-Computer Interaction
- Computer Science(all)
- Software
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ICMR '24: Proceedings of the 2024 International Conference on Multimedia Retrieval. 2024. p. 1342-1344.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - MUWS 2024
T2 - 2024 International Conference on Multimedia Retrieval, ICMR 2024
AU - Kastner, Marc A.
AU - Cheema, Gullal S.
AU - Hakimov, Sherzod
AU - Garcia, Noa
N1 - Publisher Copyright: © 2024 Copyright held by the owner/author(s).
PY - 2024/6/7
Y1 - 2024/6/7
N2 - Multimodal human understanding and analysis are emerging research areas that cut through several disciplines like Computer Vision (CV), Natural Language Processing (NLP), Speech Processing, Human-Computer Interaction (HCI), and Multimedia. Several multimodal learning techniques have recently shown the benefit of combining multiple modalities in image-text, audio-visual and video representation learning and various downstream multimodal tasks. At the core, these methods focus on modelling the modalities and their complex interactions by using large amounts of data, different loss functions and deep neural network architectures. However, for many Web and Social media applications, there is the need to model the human, including the understanding of human behaviour and perception. For this, it becomes important to consider interdisciplinary approaches, including social sciences and psychology. The core is understanding various cross-modal relations, quantifying bias such as social biases, and the applicability of models to real-world problems. Interdisciplinary theories such as semiotics or gestalt psychology can provide additional insights on perceptual understanding through signs and symbols across multiple modalities. In general, these theories provide a compelling view of multimodality and perception that can further expand computational research and multimedia applications on the Web and Social media. The theme of the MUWS workshop, multimodal human understanding, includes various interdisciplinary challenges related to social bias analyses, multimodal representation learning, detection of human impressions or sentiment, hate speech, sarcasm in multimodal data, multimodal rhetoric and semantics, and related topics. The MUWS workshop is an interactive event and includes keynotes by relevant experts, a poster session, research presentations and discussion.
AB - Multimodal human understanding and analysis are emerging research areas that cut through several disciplines like Computer Vision (CV), Natural Language Processing (NLP), Speech Processing, Human-Computer Interaction (HCI), and Multimedia. Several multimodal learning techniques have recently shown the benefit of combining multiple modalities in image-text, audio-visual and video representation learning and various downstream multimodal tasks. At the core, these methods focus on modelling the modalities and their complex interactions by using large amounts of data, different loss functions and deep neural network architectures. However, for many Web and Social media applications, there is the need to model the human, including the understanding of human behaviour and perception. For this, it becomes important to consider interdisciplinary approaches, including social sciences and psychology. The core is understanding various cross-modal relations, quantifying bias such as social biases, and the applicability of models to real-world problems. Interdisciplinary theories such as semiotics or gestalt psychology can provide additional insights on perceptual understanding through signs and symbols across multiple modalities. In general, these theories provide a compelling view of multimodality and perception that can further expand computational research and multimedia applications on the Web and Social media. The theme of the MUWS workshop, multimodal human understanding, includes various interdisciplinary challenges related to social bias analyses, multimodal representation learning, detection of human impressions or sentiment, hate speech, sarcasm in multimodal data, multimodal rhetoric and semantics, and related topics. The MUWS workshop is an interactive event and includes keynotes by relevant experts, a poster session, research presentations and discussion.
KW - human understanding
KW - image-text relations
KW - machine learning
KW - multimodality
KW - semiotics
KW - social media
KW - web
UR - http://www.scopus.com/inward/record.url?scp=85199205906&partnerID=8YFLogxK
U2 - 10.1145/3652583.3658893
DO - 10.1145/3652583.3658893
M3 - Conference contribution
AN - SCOPUS:85199205906
SP - 1342
EP - 1344
BT - ICMR '24
Y2 - 10 June 2024 through 14 June 2024
ER -