LIUM-CVC Submissions for WMT17 Multimodal Translation Task
LIUM-CVC Submissions for WMT17 Multimodal Translation Task
This paper describes the monomodal and multimodal Neural Machine Translation systems developed by LIUM and CVC for WMT17 Shared Task on Multimodal Translation. We mainly explored two multimodal architectures where either global visual features or convolutional feature maps are integrated in order to benefit from visual context. Our final systems ranked first for both En-De and En-Fr language pairs according to the automatic evaluation metrics METEOR and BLEU.
Walid Aransa、Mercedes Garc¨aa-Mart¨anez、Joost van de Weijer、Marc Masana、Luis Herranz、Adrien Bardet、Lo?c Barrault、Ozan Caglayan、Fethi Bougares
计算技术、计算机技术
Walid Aransa,Mercedes Garc¨aa-Mart¨anez,Joost van de Weijer,Marc Masana,Luis Herranz,Adrien Bardet,Lo?c Barrault,Ozan Caglayan,Fethi Bougares.LIUM-CVC Submissions for WMT17 Multimodal Translation Task[EB/OL].(2017-07-14)[2025-08-10].https://arxiv.org/abs/1707.04481.点此复制
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