WebThe recent multimodal fusion schemes combines multiple modalities as a tensor and either obtain the common information by training a feed-forward neural network, or they obtain unique... Web1% VS 100%: Parameter-Efficient Low Rank Adapter for Dense Predictions Dongshuo Yin · Yiran Yang · Zhechao Wang · Hongfeng Yu · kaiwen wei · Xian Sun MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation Models Dohwan Ko · Joonmyung Choi · Hyeong Kyu Choi · Kyoung-Woon On · Byungseok Roh · Hyunwoo Kim

Query-Driven Knowledge Base Completion using Multimodal Path Fusion …

WebIn this paper, we propose the Low-rank Multimodal Fusion method, which performs multimodal fusion using low-rank tensors to improve efficiency. We evaluate our … WebIn this paper, we propose the Low-rank Multimodal Fusion method, which performs multimodal fusion using low-rank tensors to improve efficiency. We evaluate our … jeans to shorts

Efficient Low-rank Multimodal Fusion With Modality-Specific Factors

WebIn this paper, we propose an interpretable model called Interpretable Multimodal Capsule Fusion (IMCF) which integrates routing mechanism of Capsule Network (CapsNet) and Long Short-Term Memory (LSTM) to produce refined … WebPrediction of posterior capsular opacification based on heterogeneous low-rank multimodal fusion network: Zhi-gang CHEN1(),Yong-jing WAN1,*(),Yu-lan WANG2,Cui-ling … Web13 apr. 2024 · In MSA, better fusion of modalities can help model to perform better, and multimodal fusion has been widely studied such as Tensor Fusion Network (TFN) , Low-rank Multimodal Fusion (LMF) and Memory Fusion Network (MFN) . However, those multimodal fusion methods also cause some problems such as oversized framework or … owen cheatham