no code implementations • 14 Dec 2023 • Yabing Wang, Fan Wang, Jianfeng Dong, Hao Luo
Cross-lingual cross-modal retrieval has garnered increasing attention recently, which aims to achieve the alignment between vision and target language (V-T) without using any annotated V-T data pairs.
no code implementations • 11 Sep 2023 • Yabing Wang, Shuhui Wang, Hao Luo, Jianfeng Dong, Fan Wang, Meng Han, Xun Wang, Meng Wang
Therefore, we propose Dual-view Curricular Optimal Transport (DCOT) to learn with noisy correspondence in CCR.
1 code implementation • 26 Aug 2022 • Yabing Wang, Jianfeng Dong, Tianxiang Liang, Minsong Zhang, Rui Cai, Xun Wang
In this paper, we propose a noise-robust cross-lingual cross-modal retrieval method for low-resource languages.
1 code implementation • 23 Jan 2022 • Jianfeng Dong, Yabing Wang, Xianke Chen, Xiaoye Qu, Xirong Li, Yuan He, Xun Wang
In this work, we concentrate on video representation learning, an essential component for text-to-video retrieval.
no code implementations • 2 Feb 2021 • Qi Zheng, Jianfeng Dong, Xiaoye Qu, Xun Yang, Yabing Wang, Pan Zhou, Baolong Liu, Xun Wang
The language-based setting of this task allows for an open set of target activities, resulting in a large variation of the temporal lengths of video moments.