  There are many limitations applying object detection algorithm on various
environments. Especially detecting small objects is still challenging because
they have low resolution and limited information. We propose an object
detection method using context for improving accuracy of detecting small
objects. The proposed method uses additional features from different layers as
context by concatenating multi-scale features. We also propose object detection
with attention mechanism which can focus on the object in image, and it can
include contextual information from target layer. Experimental results shows
that proposed method also has higher accuracy than conventional SSD on
detecting small objects. Also, for 300$\times$300 input, we achieved 78.1% Mean
Average Precision (mAP) on the PASCAL VOC2007 test set.
