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What's in the Flow? Exploiting Temporal Motion Cues for Unsupervised Generic Event Boundary Detection
May 1, 2024, 4:45 a.m. | Sourabh Vasant Gothe, Vibhav Agarwal, Sourav Ghosh, Jayesh Rajkumar Vachhani, Pranay Kashyap, Barath Raj Kandur Raja
cs.CV updates on arXiv.org arxiv.org
Abstract: Generic Event Boundary Detection (GEBD) task aims to recognize generic, taxonomy-free boundaries that segment a video into meaningful events. Current methods typically involve a neural model trained on a large volume of data, demanding substantial computational power and storage space. We explore two pivotal questions pertaining to GEBD: Can non-parametric algorithms outperform unsupervised neural methods? Does motion information alone suffice for high performance? This inquiry drives us to algorithmically harness motion cues for identifying generic …
abstract arxiv computational cs.cv current data detection event events flow free power segment space storage taxonomy temporal type unsupervised video
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