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Search results with tag "Convolutional features"
Learning Deep Features for Discriminative Localization
cnnlocalization.csail.mit.eduweights of the output layer on to the convolutional feature maps, a technique we call class activation mapping. As illustrated in Fig. 2, global average pooling outputs the spatial average of the feature map of each unit at the last convolutional layer. A weighted sum of these values is used to generate the final output. Similarly, we compute a
BASNet: Boundary-Aware Salient Object Detection
openaccess.thecvf.comas well as aggregating multi-level convolutional features in (Amulet) [74] for saliency detection. Hu et al. [18] pro-posed to learn a Level Set [48] function to output accurate boundaries and compact saliency. Luo et al. [41] designed a network (NLDF+) with a 4×5 grid structure to combine local and global information and used a fusing loss of ...