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Jun 9, 2022 · The main challenge in the field of unsupervised machine translation (UMT) is to associate source-target sentences in the latent space.
In this paper, we employ a spatial-temporal graph obtained from videos to exploit object interactions in space and time for disambiguation purposes.
Abstract—The main challenge in the field of unsupervised machine translation (UMT) is to associate source-target sentences in the latent space.
This model employs multi-modal back-translation and features pseudo-visual pivoting, in which it learns a shared multilingual visual-semantic embedding ...
6 days ago · Unsupervised multimodal machine translation. (UMMT) aims to leverage vision information as a pivot between two languages to achieve.
Nov 8, 2024 · Unsupervised multimodal machine translation (UMMT) aims to leverage vision information as a pivot between two languages to achieve better ...
Missing: Video | Show results with:Video
This model employs multimodal back-translation and features pseudo visual pivoting in which it learns a shared multilingual visual-semantic embedding space ...
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Jun 9, 2022 · "Video pivoting unsupervised multi-modal machine translation." IEEE Transactions on Pattern Analysis and Machine Intelligence (2022).
Sep 29, 2024 · This paper proposes a visual pivoting UMMT method in low-resource DLPs. Specifically, we first construct a dataset containing two DLPs including English-Uyghur ...
We propose an unsupervised multi-modal machine translation (UMNMT) framework based on the language translation cycle con- sistency loss conditional on the image ...
Missing: Pivoting | Show results with:Pivoting