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ADVERSARIAL UNSUPERVISED VIDEO SUMMARIZATION AUGMENTED WITH DICTIONARY LOSS

Kaseris, Michail; Mademlis, Ioannis; Pitas, Ioannis;
Open Access
  • Publisher: Zenodo
Abstract
Automated unsupervised video summarization by key-frame extraction consists in identifying representative video frames, best abridging a complete input sequence, and temporally ordering them to form a video summary, without relying on manually constructed ground-truth key-frame sets. State-of-the-art unsupervised deep neural approaches consider the desired summary to be a subset of the original sequence, composed of video frames that are sufficient to visually reconstruct the entire input. They typically employ a pre-trained CNN for extracting a vector representation per RGB video frame and a baseline LSTM adversarial learning framework for identifying key-frame...
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Provider: ZENODO
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