Icdv-30037
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Temporal Dynamics and Semantic Consistency: A Novel Framework for Unsupervised Video Summarization
The proposed TSAN consists of three main components: an Encoder, a Selector, and a Discriminator. Linking the content to specific technical data, such
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Generative Adversarial Networks (GANs) have achieved remarkable success in image synthesis. Recently, adversarial loss has been applied to video tasks, such as video generation and future frame prediction. We draw inspiration from these works, applying adversarial training to the selector mechanism in summarization, forcing the model to select frames that "fool" a discriminator trained on global video semantics.