Papers by Joo Lim

1 papers
GazeVQA: A Video Question Answering Dataset for Multiview Eye-Gaze Task-Oriented Collaborations (2023.emnlp-main)

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Challenge: Existing studies on the use of exocentric and egocentric videos in video question answering are focusing on eye-gaze information.
Approach: They propose a task-oriented VQA dataset that captures eye-gaze information . they propose assisting models that ground the perceptual input into semantic information based on three different answer types .
Outcome: The proposed model can ground the perceptual input into semantic information while reducing ambiguities.

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