In this work, the multiway multimodal transformer. (MMT) is proposed to simultaneously explore mul- tiway multimodal intercorrelations for each modal- ity via ...
The core idea of MMT is the multiway multimodal attention, where the multiple modalities are leveraged to compute the multiway attention tensor. This naturally ...
The core idea of MMT is the multiway multimodal attention, where the multiple modalities are leveraged to compute the multiway attention tensor. This naturally ...
Our proposed Multi-Modal Transformer (MMT) aggregates sequences of multi-modal features (e.g. appearance, motion, audio, OCR, etc.) from a video. It then embeds ...
In this paper, we introduce the multimodal self-attention in Transformer to solve the issues above in MMT. The proposed method learns the representation of ...
Missing: Learning. | Show results with:Learning.
Nov 15, 2022 · In this work, we develop a multiscale multimodal Transformer (MMT) that employs hierarchical representation learning. Particularly, MMT is ...
Mar 19, 2021 · It allows in a natural way to process the temporal dependencies inside the multi modal data source. To train a text to video retrieval neural ...
To tackle this sub-challenge, we propose a method called MMT-GD, which leverages a multimodal transformer model to effectively integrate the multimodal data.
Oct 22, 2024 · In this work, we propose a two-step beam management method by combining MMT with RL for dynamic beam index prediction. In the first step, we ...
In this paper, we introduce the multimodal self-attention in Transformer to solve the issues above in MMT. The proposed method learns the representation of ...
Missing: way Multi-