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Scene Attribute Semantic Relational Regularization for Transport-travel Scene Understanding
2020
IEEE Access
Attribute learning has improved the performance in scene understanding and scene recognition. However, there are many attributes described by words or short texts in a static scene and traffic crowd scene. If there are two similar scenes, the semantic relationship topology structures of corresponding attribute groups of the two scenes are also homogeneity. But it is difficult to learn a semantic relation topology projection across semantic text data and visual data. To solve the problem, we
doi:10.1109/access.2020.3001294
fatcat:jvtr22of5jaqbkkphfnrzkci7i