Mukea: Multimodal knowledge extraction and accumulation for knowledge-based visual question answering
Abstract Knowledge-based visual question answering requires the ability of associating
external knowledge for open-ended cross-modal scene understanding. One limitation of …
external knowledge for open-ended cross-modal scene understanding. One limitation of …
A unified end-to-end retriever-reader framework for knowledge-based vqa
Knowledge-based Visual Question Answering (VQA) expects models to rely on external
knowledge for robust answer prediction. Though significant it is, this paper discovers several …
knowledge for robust answer prediction. Though significant it is, this paper discovers several …
Resolving zero-shot and fact-based visual question answering via enhanced fact retrieval
Practical applications with visual question answering (VQA) systems are challenging, and
recent research has aimed at investigating this important field. Many issues related to real …
recent research has aimed at investigating this important field. Many issues related to real …
Semantic collaborative learning for cross-modal moment localization
Localizing a desired moment within an untrimmed video via a given natural language query,
ie, cross-modal moment localization, has attracted widespread research attention recently …
ie, cross-modal moment localization, has attracted widespread research attention recently …
HybridPrompt: bridging language models and human priors in prompt tuning for visual question answering
Z Ma, Z Yu, J Li, G Li - Proceedings of the AAAI Conference on Artificial …, 2023 - ojs.aaai.org
Abstract Visual Question Answering (VQA) aims to answer the natural language question
about a given image by understanding multimodal content. However, the answer quality of …
about a given image by understanding multimodal content. However, the answer quality of …
Exploiting the Social-Like Prior in Transformer for Visual Reasoning
Benefiting from instrumental global dependency modeling of self-attention (SA), transformer-
based approaches have become the pivotal choices for numerous downstream visual …
based approaches have become the pivotal choices for numerous downstream visual …
Scenegate: Scene-graph based co-attention networks for text visual question answering
Visual Question Answering (VQA) models fail catastrophically on questions related to the
reading of text-carrying images. However, TextVQA aims to answer questions by …
reading of text-carrying images. However, TextVQA aims to answer questions by …
Multimodal Bi-direction guided attention networks for visual question answering
L Cai, N Xu, H Tian, K Chen, H Fan - Neural Processing Letters, 2023 - Springer
Current visual question answering (VQA) has become a research hotspot in the computer
vision and natural language processing field. A core solution of VQA is how to fuse multi …
vision and natural language processing field. A core solution of VQA is how to fuse multi …
Bridging the Cross-Modality Semantic Gap in Visual Question Answering
The objective of visual question answering (VQA) is to adequately comprehend a question
and identify relevant contents in an image that can provide an answer. Existing approaches …
and identify relevant contents in an image that can provide an answer. Existing approaches …
Boosting Visual Question Answering Through Geometric Perception and Region Features
H Yu, Z Wang, Y Liu, H Liu - ECAI 2023, 2023 - ebooks.iospress.nl
Visual question answering (VQA) is a crucial yet challenging task in multimodal
understanding. To correctly answer questions about an image, VQA models are required to …
understanding. To correctly answer questions about an image, VQA models are required to …