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Detecting Attended Visual Targets in Video
[article]
2020
arXiv
pre-print
We address the problem of detecting attention targets in video. Our goal is to identify where each person in each frame of a video is looking, and correctly handle the case where the gaze target is out-of-frame. Our novel architecture models the dynamic interaction between the scene and head features and infers time-varying attention targets. We introduce a new annotated dataset, VideoAttentionTarget, containing complex and dynamic patterns of real-world gaze behavior. Our experiments show that
arXiv:2003.02501v2
fatcat:72jamucspnb3hpthu2zdqz77bq