HiTeA: Hierarchical Temporal-Aware Video-Language Pre-training

Author:

Ye Qinghao1,Xu Guohai1,Yan Ming1,Xu Haiyang1,Qian Qi1,Zhang Ji1,Huang Fei1

Affiliation:

1. Alibaba Group,DAMO Academy

Publisher

IEEE

Reference62 articles.

1. Localizing Moments in Video with Natural Language

2. Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval

3. Is space-time attention all you need for video understanding?;Bertasius

4. Revisiting the “Video” in Video-Language Understanding

5. Collecting highly parallel data for paraphrase evaluation;Chen

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1. Normality learning reinforcement for anomaly detection in surveillance videos;Knowledge-Based Systems;2024-08

2. M 2 -RAAP: A Multi-Modal Recipe for Advancing Adaptation-based Pre-training towards Effective and Efficient Zero-shot Video-text Retrieval;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

3. CapFormer: A Space-Time Video Description Model using Joint-Attention Transformer;2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC);2023-10-31

4. RTQ: Rethinking Video-language Understanding Based on Image-text Model;Proceedings of the 31st ACM International Conference on Multimedia;2023-10-26

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