Cross-Lingual Cross-Modal Consolidation for Effective Multilingual Video Corpus Moment Retrieval (2022.findings-naacl)
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| Challenge: | Existing multilingual video corpus moment retrieval methods are based on a two-stream structure. |
| Approach: | They propose a multilingual video corpus moment retrieval task that uses a two-stream structure to generate a query-visual similarity and a subtitle stream exploits the query-subtitle similarity. |
| Outcome: | The proposed method improves accuracy on a large-scale video corpus moment retrieval dataset. |
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| Challenge: | mTVR is a multilingual video moment retrieval dataset with 218K queries in English and Chinese . Various datasets have been proposed or adapted for the task, but they are all created for a single language (English). |
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Guanhua Chen, Lu Hou, Yun Chen, Wenliang Dai, Lifeng Shang, Xin Jiang, Qun Liu, Jia Pan, Wenping Wang
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| Challenge: | Existing methods to learn multimodal multilingual embeddings for text and image retrieval tasks are limited to English. |
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