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Camouflaged objects are generally difficult to be detected in their natural environment even for human beings.
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2015
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T. V. Nguyen and J. Sepulveda, “Salient object detection via augmented hypotheses,” in Proceedings of the International Joint Conference on Artificial Intelligence , 2015, pp. 2176–2182
2015
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2015
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2015
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S. Zheng, S. Jayasumana, B. Romera-Paredes, V. Vineet, Z. Su, D. Du, C. Huang, and P. H. S. Torr, “Conditional random fields as recurrent neural networks,” in IEEE International Conference on Computer Vision , 2015, pp. 1529–1537
2015
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L. Prasad, “Outsmarting the art of camouflage,” Discover Magazine , 2016, available online at http://blogs.discovermagazine.com/crux/2016/11/02/outsmarting-the-art-of-camouflage/
2016
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K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Conference on Computer Vision and Pattern Recognition , 2016, pp. 770–778
2016
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F. Xue, C. Yong, S. Xu, H. Dong, Y. Luo, and W. Jia, “Camouflage performance analysis and evaluation framework based on features fusion,” Multimedia Tools and Applications , vol. 75, no. 7, pp. 4065–4082, Apr 2016
2016
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N. Liu and J. Han, “Dhsnet: Deep hierarchical saliency network for salient object detection,” in IEEE Conference on CVPR , 2016, pp. 678–686
2016
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K. He, G. Gkioxari, P. Dollár, and R. Girshick, “Mask r-cnn,” in International Conference on Computer Vision , 2017, pp. 2980–2988
2017
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S. Xie, R. B. Girshick, P. Dollár, Z. Tu, and K. He, “Aggregated residual transformations for deep neural networks,” in IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 5987–5995
2017
Cited alongside, same era.
T. V. Nguyen, Q. Zhao, and S. Yan, “Attentive systems: A survey,” International Journal of Computer Vision , vol. 126, no. 1, pp. 86–110, 2018
2018
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T. Le, T. V. Nguyen, Z. Nie, M. Tran, and A. Sugimoto, “Anabranch network for camouflaged object segmentation,” Computer Vision and Image Understanding , vol. 184, pp. 45–56, 2019
2019
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M. A. Alcorn, Q. Li, Z. Gong, C. Wang, L. Mai, W.-S. Ku, and A. Nguyen, “Strike (with) a pose: Neural networks are easily fooled by strange poses of familiar objects,” in Conf. on Computer Vision and Pattern Recognition , 2019
2019
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J.-X. Zhao, J.-J. Liu, D.-P. Fan, Y. Cao, J. Yang, and M.-M. Cheng, “Egnet: Edge guidance network for salient object detection,” in Proceedings of the IEEE International Conference on Computer Vision , 2019, pp. 8779–8788
2019
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Z. Wu, L. Su, and Q. Huang, “Cascaded partial decoder for fast and accurate salient object detection,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 3907–3916
2019
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T. Zhao and X. Wu, “Pyramid feature attention network for saliency detection,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 3085–3094
2019
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X. Qin, Z. Zhang, C. Huang, C. Gao, M. Dehghan, and M. Jagersand, “Basnet: Boundary-aware salient object detection,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 7479–7489
2019
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T.-N. Le and A. Sugimoto, “Semantic instance meets salient object: Study on video semantic salient instance segmentation,” in IEEE Winter Conference on Applications of Computer Vision , 2019, pp. 1779–1788
2019
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T. V. Nguyen, K. Nguyen, and T. Do, “Semantic prior analysis for salient object detection,” IEEE Transactions on Image Processing , vol. 28, no. 6, pp. 3130–3141, 2019
2019
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Z. Huang, L. Huang, Y. Gong, C. Huang, and X. Wang, “Mask scoring r-cnn,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 6409–6418
2019
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J.-J. Liu, Q. Hou, M.-M. Cheng, J. Feng, and J. Jiang, “A simple pooling-based design for real-time salient object detection,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 3917–3926
2019
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K. Chen, J. Pang, J. Wang, Y. Xiong, X. Li, S. Sun, W. Feng, Z. Liu, J. Shi, W. Ouyang et al. , “Hybrid task cascade for instance segmentation,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2019, pp. 4974–4983
2019
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T.-N. Le, A. Sugimoto, S. Ono, and H. Kawasaki, “Attention r-cnn for accident detection,” in IEEE Intelligent Vehicles Symposium , 2020
2020
Closest in time.
D.-P. Fan, G.-P. Ji, G. Sun, M.-M. Cheng, J. Shen, and L. Shao, “Camouflaged object detection,” in IEEE Conference on Computer Vision and Pattern Recognition , 2020
2020
Closest in time.
T.-N. Le, V. Nguyen, C. Le, T.-C. Nguyen, M.-T. Tran, and T. V. Nguyen, “Camoufinder: Finding camouflaged instances in images,” in AAAI Conference on Artificial Intelligence , 2021, pp. 1–4
2021
Closest in time.