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Modulated Fusion using Transformer for Linguistic-Acoustic Emotion Recognition
This paper aims to bring a new lightweight yet powerful solution for the...
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A Transformer-based joint-encoding for Emotion Recognition and Sentiment Analysis
Understanding expressed sentiment and emotions are two crucial factors i...
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Can adversarial training learn image captioning ?
Recently, generative adversarial networks (GAN) have gathered a lot of i...
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Modulated Self-attention Convolutional Network for VQA
As new data-sets for real-world visual reasoning and compositional quest...
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Adversarial reconstruction for Multi-modal Machine Translation
Even with the growing interest in problems at the intersection of Comput...
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Object-oriented Targets for Visual Navigation using Rich Semantic Representations
When searching for an object humans navigate through a scene using seman...
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Bringing back simplicity and lightliness into neural image captioning
Neural Image Captioning (NIC) or neural caption generation has attracted...
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UMONS Submission for WMT18 Multimodal Translation Task
This paper describes the UMONS solution for the Multimodal Machine Trans...
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Transformer for Emotion Recognition
This paper describes the UMONS solution for the OMG-Emotion Challenge. W...
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Modulating and attending the source image during encoding improves Multimodal Translation
We propose a new and fully end-to-end approach for multimodal translatio...
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Visually Grounded Word Embeddings and Richer Visual Features for Improving Multimodal Neural Machine Translation
In Multimodal Neural Machine Translation (MNMT), a neural model generate...
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An empirical study on the effectiveness of images in Multimodal Neural Machine Translation
In state-of-the-art Neural Machine Translation (NMT), an attention mecha...
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Multimodal Compact Bilinear Pooling for Multimodal Neural Machine Translation
In state-of-the-art Neural Machine Translation, an attention mechanism i...
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