Learning Semantic Feature Map for Visual Content Recognition



The spatial relationship among objects provide rich clues to object contexts for visual recognition. In this paper, we propose to learn Semantic Feature Map (SFM) by deep neural networks to model the spatial object contexts for better understanding of image and video contents. Specifically, we first extract high-level semantic object features on input image with convolutional neural networks for every object proposals, and organize them to the designed SFM so that spatial information among objects are preserved...