Dynamic fusion with intra-and inter-modality attention flow for visual question answering

• Main Authors: GAO, Peng, JIANG, Zhengkai, YOU, Haoxuan, LU, Pan, HOI, Steven C. H., WANG, Xiaogang, LI, Hongsheng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Vision + Language; Vision Applications and Systems; Visual Reasoning; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/5260; https://ink.library.smu.edu.sg/context/sis_research/article/6263/viewcontent/Gao_Dynamic_Fusion_With_Intra__and_Inter_Modality_Attention_Flow_for_Visual_CVPR_2019_paper.pdf
• Institution: Singapore Management University

Learning effective fusion of multi-modality features is at the heart of visual question answering. We propose a novel method of dynamically fusing multi-modal features with intra- and inter-modality information flow, which alternatively pass dynamic information between and across the visual and language modalities. It can robustly capture the high-level interactions between language and vision domains, thus significantly improves the performance of visual question answering. We also show that the proposed dynamic intra-modality attention flow conditioned on the other modality can dynamically modulate the intramodality attention of the target modality, which is vital for multimodality feature fusion. Experimental evaluations on the VQA 2.0 dataset show that the proposed method achieves state-of-the-art VQA performance. Extensive ablation studies are carried out for the comprehensive analysis of the proposed method.