Video Retrieval
Video retrieval focuses on efficiently and accurately finding relevant video segments or entire videos from massive datasets using text or other video queries. Current research emphasizes improving retrieval speed and accuracy through innovative model architectures like Transformers and graph neural networks, often incorporating contrastive learning and techniques to handle partially relevant videos or noisy data. These advancements are crucial for applications ranging from e-commerce and autonomous driving to scientific research involving large video corpora, enabling more effective analysis and information access.
Papers
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