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Published in:
2023 | OriginalPaper | Chapter
8. Conditional Siamese Convolutional Network
Authors : Avik Hati, Rajbabu Velmurugan, Sayan Banerjee, Subhasis Chaudhuri
Published in: Image Co-segmentation
Publisher: Springer Nature Singapore
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Abstract
This chapter describes a deep convolutional neural network-based co-segmentation model through an end-to-end training of a conditional siamese encoder-decoder network. The network is composed of a pair of VGG-16-based encoder-decoder network with shared weights, a metric learning network and a decision network. The metric learning network finds an optimum latent feature space where objects of the same class are closer and that of different classes are separated by a certain margin. Depending on the extracted features, the decision network predicts the presence or absence of common objects in the input image pair, and the encoder-decoder network produces co-segmentation masks accordingly. The model is completely class agnostic and does not require any semantic information.