Yugang Li1, 2, *, Yongbin Wang1, Zhe Chen2, Yuting Zhu3
CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1575-1589, 2020, DOI:10.32604/cmc.2020.07451
Abstract Understanding an image goes beyond recognizing and locating the objects in it,
the relationships between objects also very important in image understanding. Most
previous methods have focused on recognizing local predictions of the relationships. But
real-world image relationships often determined by the surrounding objects and other
contextual information. In this work, we employ this insight to propose a novel
framework to deal with the problem of visual relationship detection. The core of the
framework is a relationship inference network, which is a recurrent structure designed for
combining the global contextual information of the object to infer the relationship of the… More >
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