Modeling Multimodal Social Interactions: New Challenges and Baselines with Densely Aligned Representations

• URL: http://arxiv.org/abs/2403.02090v3
• Date: Mon, 29 Apr 2024 12:16:04 GMT
• Title: Modeling Multimodal Social Interactions: New Challenges and Baselines with Densely Aligned Representations
• Authors: Sangmin Lee, Bolin Lai, Fiona Ryan, Bikram Boote, James M. Rehg,
• Abstract summary: We introduce three new challenges to model the fine-grained dynamics between multiple people: speaking target identification, pronoun coreference resolution, and mentioned player prediction. We propose a novel multimodal baseline that leverages densely aligned language-visual representations by synchronizing visual features with their corresponding utterances. Experiments demonstrate the effectiveness of the proposed approach with densely aligned multimodal representations in modeling fine-grained social interactions.
• Score: 20.848802791989307
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Understanding social interactions involving both verbal and non-verbal cues is essential for effectively interpreting social situations. However, most prior works on multimodal social cues focus predominantly on single-person behaviors or rely on holistic visual representations that are not aligned to utterances in multi-party environments. Consequently, they are limited in modeling the intricate dynamics of multi-party interactions. In this paper, we introduce three new challenging tasks to model the fine-grained dynamics between multiple people: speaking target identification, pronoun coreference resolution, and mentioned player prediction. We contribute extensive data annotations to curate these new challenges in social deduction game settings. Furthermore, we propose a novel multimodal baseline that leverages densely aligned language-visual representations by synchronizing visual features with their corresponding utterances. This facilitates concurrently capturing verbal and non-verbal cues pertinent to social reasoning. Experiments demonstrate the effectiveness of the proposed approach with densely aligned multimodal representations in modeling fine-grained social interactions. Project website: https://sangmin-git.github.io/projects/MMSI.

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