The extraction of context among the neighboring utterances and considering the importance of inter-modal utterances before multimodal fusion are the most important research issues in this field. This article presents a novel approach to extract the context at multiple levels and to understand the ...
Thus, we propose the TBSFF-UNet (Three-Branch Feature Fusion UNet) model, which introduces novel skip connections to integrate diverse semantic levels. This facilitates the aggregation of information, enabling the capture of richer semantic details even at lower feature layers, subsequently forwarded ...
In the multi-modal fusion stage, the goal is to fuse the acoustic and visual features, learning the relationship between both. To do so, we rely on a six-block transformer encoder that ingests an audio-visual (AV) embedding. We construct the AV embedding by concatenating both modalities tem...
As a result, multi-data fusion-based methods have emerged as a trend in predicting the DLCI. To facilitate research in the field of the DLCI prediction, Jain et al. created the publicly available Brain4Cars dataset, which encompasses driver face videos, driving scene videos, vehicle dynamics,...
Joint multimodal entity-relation extraction based on edge-enhanced graph alignment network and word-pair relation tagging. In Proceedings of the AAAI Conference on Artificial Intelligence, Washington, DC, USA, 7–14 February 2023; Volume 37, pp. 11051–11059. [Google Scholar] Fabregat, H.; ...
Fusion Search Overview Development Guidelines Data Storage Management Data Storage Management Overview Data Storage Management Development Guidelines Atomic Service Atomic Service Overview What Is an Atomic Service Atomic Service Features Atomic Service Experience Service Discovery Se...
This paper aims to address the challenges of identifying and predicting user scenario and behavior sequences through a multimodal data fusion approach, focusing on the integration of visual and environmental data to capture subtle scenario and behavioral features. For the purpose, a novel Vision-...
Multimodal Input Standard Event Development Guidelines Media Video Video Overview Development Guidelines for Codec Capability Query Development Guidelines on Video Encoding and Decoding Development Guidelines on Video Playback Development Guidelines on Video Recording Development Guidelines on Vide...
Deep learning-basedmultimodal ERC has achieved great succ... C Xu,Y Du,LZ Yuan - 《Computational Intelligence》 被引量: 0发表: 2024年 A novel facial expression recognition model based on harnessing complementary features in multi-scale network with attention fusion paper presents a novel method ...
Feichtenhofer C, Pinz A, Zisserman A (2016) Convolutional two-stream network fusion for video action recognition Diba A, Sharma V, Van Gool L (2017) Deep temporal linear encoding networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2329–2338 ...