2、Tensor Fusion Network 我们提出的TFN由三个主要部分组成: 1)模态嵌入子网络以单模态特征作为输入,并输出丰富的模态嵌入。 2)张量融合层使用模态嵌入的3-fold笛卡尔积显式地模拟单模态、双模态和三模态相互作用。 3)情感推理子网络是以张量融合层的输出为条件进行情感推理的网络。 2.1 Modality Embedding Subnetw...
模态内的动态变化:对口语化的文本文件进行情感分析非常困难。 因此,为了应对这两个挑战,作者提出了一种新的模型Tensor Fusion Network(张量融合网络,TFN),TFN能够端到端地学习模态内和模态间的动态,采用一种新的多模态融合方法(张量融合)对模态间动态进行建模,模态内动态则通过三个模态嵌入子网络进行建模。
or late fusion (vote, etc.) which can not well study the interactions between multiple modalities. To address this, we propose a framework named ML-TFN (Multi Layers Tensor Fusion Network) to model the inter-modality dynamics through Tensor Fusion Network. Specifically, Tensor Fusion approach ...
TFNTensor Fusion Network LMFLow-rank Multi-modal Fusion MFBMulti-modal Factorized Bilinear pooling MuLTMulti-modal Transformer LMF-MulTLow-Rank Fusion-based Transformer for Multi-modal Sequences MFNMemory Fusion Network MFMMulti-modal Factorized Multilinear ...
3. Proposed Audio-Visual Tensor Fusion Network Recall fromSection 1that this study proposes an AV-TFN, the first deep learning-based piano playing posture classification method using audio-visual information.Figure 3demonstrates the overall process of AV-TFN. We first (a) collect the C3Pap dataset...