Deeply Activated Salient Region for Instance Search

Due to the lack of suitable feature representation, effective solution to the instance search is still slow to occur. In this paper, a novel instance-level feature descriptor is proposed. The feature is built upon the salient instance region that is activated by a layer-wise back-propagation process. Such kind of region usually covers the major part an instance and represents the common patterns shared among instances of the same category. The back-propagation starts from the last convolution layer of pre-trained CNN that is originally used for classification. This makes the feature representation remain effective for instances from both known and unknown categories. Moreover, experiments show that it is effective for instance as well as image search tasks.