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Explicit Knowledge-based Reasoning for Visual Question Answering
Peng Wang, Qi Wu, Chunhua Shen +2
We describe a method for visual question answering which is capable of reasoning about contents of an image on the basis of information extracted from a large-scale knowledge base.…
Ask Me Anything: Free-form Visual Question Answering Based on Knowledge from External Sources
Qi Wu, Peng Wang, Chunhua Shen +2
We propose a method for visual question answering which combines an internal representation of the content of an image with information extracted from a general knowledge base to a…
Cross-convolutional-layer Pooling for Image Recognition
Lingqiao Liu, Chunhua Shen, Anton van den Hengel
Recent studies have shown that a Deep Convolutional Neural Network (DCNN) pretrained on a large image dataset can be used as a universal image descriptor, and that doing so leads t…
What value do explicit high level concepts have in vision to language problems?
Qi Wu, Chunhua Shen, Lingqiao Liu +2
Much of the recent progress in Vision-to-Language (V2L) problems has been achieved through a combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs…
Efficient piecewise training of deep structured models for semantic segmentation
Guosheng Lin, Chunhua Shen, Anton van dan Hengel +1
Recent advances in semantic image segmentation have mostly been achieved by training deep convolutional neural networks (CNNs). We show how to improve semantic segmentation through…
Light axial vector mesons
Kan Chen, Cheng-Qun Pang, Xiang Liu +1
Inspired by the abundant experimental observation of axial-vector states, we study whether the observed axial-vector states can be categorized into the conventional axial-vector me…