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Semantic Aware Attention Based Deep Object Co-segmentation

  • Hong Chen
  • Yifei HuangEmail author
  • Hideki Nakayama
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11364)

Abstract

Object co-segmentation is the task of segmenting the same objects from multiple images. In this paper, we propose the Attention Based Object Co-Segmentation for object co-segmentation that utilize a novel attention mechanism in the bottleneck layer of the deep neural network for the selection of semantically related features. Furthermore, we take the benefit of attention learner and propose an algorithm to segment multi-input images in linear time complexity. Experiment results demonstrate that our model achieves state of the art performance on multiple datasets, with a significant reduction of computational time.

Keywords

Co-segmentation Attention Deep learning 

Notes

Acknowledgements

This work was supported by JSPS KAKENHI Grant Number 16H05872.

Supplementary material

484519_1_En_27_MOESM1_ESM.pdf (17.1 mb)
Supplementary material 1 (pdf 17515 KB)

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.The University of TokyoTokyoJapan

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