Papers by Mushi Wang
DREAM: Improving Video-Text Retrieval Through Relevance-Based Augmentation Using Large Foundation Models (2025.naacl-long)
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| Challenge: | Recent advances in video-text retrieval models have limited training data annotations. |
| Approach: | They propose a Video-Text Retrieval Paradigm with Relevance-based Augmentation which enhances video and text data using large foundation models to learn more generalized features. |
| Outcome: | The proposed method improves video-text retrieval performance over existing methods. |