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The task of temporally grounding textual queries in videos is to localize one video segment that semantically corresponds to the given query.
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Tran, D., Bourdev, L., Fergus, R., Torresani, L., Paluri, M.: Learning spatiotemporal features with 3d convolutional networks. In: Proceedings of the IEEE international conference on computer vision. pp. 4489–4497 (2015)
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Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.Y., Berg, A.C.: Ssd: Single shot multibox detector. In: European conference on computer vision. pp. 21–37. Springer (2016)
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Anne Hendricks, L., Wang, O., Shechtman, E., Sivic, J., Darrell, T., Russell, B.: Localizing moments in video with natural language. In: Proceedings of the IEEE international conference on computer vision. pp. 5803–5812 (2017)
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Buch, S., Escorcia, V., Shen, C., Ghanem, B., Carlos Niebles, J.: Sst: Single-stream temporal action proposals. In: Proceedings of the IEEE conference on Computer Vision and Pattern Recognition. pp. 2911–2920 (2017)
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Gao, J., Sun, C., Yang, Z., Nevatia, R.: Tall: Temporal activity localization via language query. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 5267–5275 (2017)
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Krishna, R., Hata, K., Ren, F., Fei-Fei, L., Carlos Niebles, J.: Dense-captioning events in videos. In: Proceedings of the IEEE international conference on computer vision. pp. 706–715 (2017)
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Zhao, Y., Xiong, Y., Wang, L., Wu, Z., Tang, X., Lin, D.: Temporal action detection with structured segment networks. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 2914–2923 (2017)
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Chen, J., Chen, X., Ma, L., Jie, Z., Chua, T.S.: Temporally grounding natural sentence in video. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. pp. 162–171 (2018)
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Lee, K.H., Chen, X., Hua, G., Hu, H., He, X.: Stacked cross attention for image-text matching. In: Proceedings of the European Conference on Computer Vision (ECCV). pp. 201–216 (2018)
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Lin, T., Zhao, X., Su, H., Wang, C., Yang, M.: Bsn: Boundary sensitive network for temporal action proposal generation. In: Proceedings of the European Conference on Computer Vision (ECCV). pp. 3–19 (2018)
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Liu, B., Yeung, S., Chou, E., Huang, D.A., Fei-Fei, L., Niebles, J.C.: Temporal modular networks for retrieving complex compositional activities in videos. In: ECCV (2018)
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Lin, T., Liu, X., Li, X., Ding, E., Wen, S.: Bmn: Boundary-matching network for temporal action proposal generation. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 3889–3898 (2019)
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Mithun, N.C., Paul, S., Roy-Chowdhury, A.K.: Weakly supervised video moment retrieval from text queries. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 11592–11601 (2019)
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Wang, W., Huang, Y., Wang, L.: Language-driven temporal activity localization: A semantic matching reinforcement learning model. In: CVPR (2019)
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Liu, M., Wang, X., Nie, L., He, X., Chen, B., Chua, T.S.: Attentive moment retrieval in videos. In: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval. pp. 15–24 (2018)
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Wu, A., Han, Y.: Multi-modal circulant fusion for video-to-language and backward. In: IJCAI. vol. 3, p. 8 (2018)
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Chen, S., Jiang, Y.: Semantic proposal for activity localization in videos via sentence query. In: Proceedings of the AAAI Conference on Artificial Intelligence (2019)
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Gao, M., Davis, L., Socher, R., Xiong, C.: WSLLN: weakly supervised natural language localization networks. In: EMNLP-IJCNLP 2019, Hong Kong, China, November 3-7, 2019. pp. 1481–1487 (2019)
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Ge, R., Gao, J., Chen, K., Nevatia, R.: Mac: Mining activity concepts for language-based temporal localization. In: WACV (2019)
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2019
Cited alongside, same era.
Xu, H., He, K., Plummer, B.A., Sigal, L., Sclaroff, S., Saenko, K.: Multilevel language and vision integration for text-to-clip retrieval. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 33, pp. 9062–9069 (2019)
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Yuan, Y., Ma, L., Wang, J., Liu, W., Zhu, W.: Semantic conditioned dynamic modulation for temporal sentence grounding in videos. In: Advances in Neural Information Processing Systems. pp. 534–544 (2019)
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Yuan, Y., Mei, T., Zhu, W.: To find where you talk: Temporal sentence localization in video with attention based location regression. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 33, pp. 9159–9166 (2019)
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2020
Closest in time.
Lin, Z., Zhao, Z., Zhang, Z., Wang, Q., Liu, H.: Weakly-supervised video moment retrieval via semantic completion network (2020)
2020
Closest in time.
Wang, J., Ma, L., Jiang, W.: Temporally grounding language queries in videos by contextual boundary-aware prediction (2020)
2020
Closest in time.