ASSD: Attentive single shot multibox detector.

This paper proposes a new deep neural network for object detection. The proposed network, termed ASSD, builds feature relations in the spatial space of the feature map. With the global relation information, ASSD learns to highlight useful regions on the feature maps while suppressing the irrelevant information, thereby providing reliable guidance for object detection. Compared to methods that rely on complicated CNN layers to refine the feature maps, ASSD is simple in design and is computationally efficient. Experimental results show that ASSD competes favorably with the state-of-the-arts, including SSD, DSSD, FSSD and RetinaNet. Code is available at:. • We propose to incorporate pixel-wise feature relations into the one-stage detector. • The network preserves the simplicity and efficiency of SSD while being more accurate. • The results show that ASSD competes favorably with the state-of-the-arts. [ABSTRACT FROM AUTHOR]