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Currently, a plethora of saliency models based on deep neural networks have led great breakthroughs in many complex high-level vision tasks (e.g.
Top-down control of visual attention in object detection
A. Oliva, A. Torralba, M. S. Castelhano, and J. M. Henderson · 2003
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli · 2004
Earlier work this paper cites.
A visual attention system for object detection and goal-directed search
S. Frintrop · 2005
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Components of bottom up gaze allocation in natural images
R. Peters, A. Iyer, L. Itti, and C. Koch · 2005
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Active segmentation with fixation
A. Mishra, Y. Aloimonos, and C. L. Fah · 2009
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State-of-the-art in visual attention modeling
A. Borji and L. Itti · 2013
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Quantitative analysis of human-model agreement in visual saliency modeling: A comparative study
A. Borji, D. N. Sihite, and L. Itti · 2013
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Analysis of scores, datasets, and models in visual saliency prediction
A. Borji, H. R. Tavakoli, D. N. Sihite, and L. Itti · 2013
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Intriguing properties of neural networks
C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. J. Goodfellow, and R. Fergus · 2014
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Salicon: Reducing the semantic gap in saliency prediction by adapting deep neural networks
X. Huang, C. Shen, X. Boix, and Q. Zhao · 2015
Earlier work this paper cites.
Explaining and harnessing adversarial examples
I. Goodfellow, J. Shlens, and C. Szegedy · 2015
Earlier work this paper cites.
Salicon: Saliency in context
M. Jiang, S. Huang, J. Duan, and Q. Zhao · 2015
Earlier work this paper cites.
Dr (eye) ve: a dataset for attention-based tasks with applications to autonomous and assisted driving
S. Alletto, A. Palazzi, F. Solera, S. Calderara, and R. Cucchiara · 2016
Cited alongside, same era.
A deep multi-level network for saliency prediction
M. Cornia, L. Baraldi, G. Serra, and R. Cucchiara · 2016
Cited alongside, same era.
Shallow and deep convolutional networks for saliency prediction
J. Pan, K. McGuiness, E. Sayrol, N. Conner, and et al · 2016
Cited alongside, same era.
Adversarial examples in the physical world
A. Kurakin, I. Goodfellow, and S. Bengio · 2016
Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
Adversarial manipulation of deep representations
S. Sabour, Y. Cao, F. Faghri, and D. Fleet · 2016
Cited alongside, same era.
Universal adversarial perturbations against semantic image segmentation
J. H. Metzen, M. C. Kumar, T. Brox, and V. Fischer · 2017
Later among the works it cites.
What do different evaluation metrics tell us about saliency models?
Z. Bylinskii, T. Judd, A. Oliva, A. Torralba, and F. Durand · 2017
Later among the works it cites.
Predicting human eye fixations via an lstm-based saliency attentive model
M. Cornia, L. Baraldi, G. Serra, and et al · 2018
Later among the works it cites.
Adversarial attacks and defences competition
A. Kurakin, I. Goodfellow, S. Bengio, Y. Dong, F. Liao, M. Liang, J. Wang, and etc · 2018
Later among the works it cites.
High-resolution image synthesis and semantic manipulation with conditional gans
T. C. Wang, M. Y. Liu, J. Y. Zhu, A. Tao, J. Kautz, and B. Catanzaro · 2018
Later among the works it cites.
Deep visual attention prediction
W. Wang and J. Shen · 2018
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Full speed region sensorless drive of permanent-magnet machine combining saliency-based and back-emf-based drive
S. C. Yang and Y. L. Hsu · 2017
Cited alongside, same era.
Salgan: Visual saliency prediction with generative adversarial networks
J. Pan, C. Canton, K. McGuinness, and et al · 2017
Cited alongside, same era.
Towards evaluating the robustness of neural networks
N. Carlini and D. Wagner · 2017
Cited alongside, same era.
Adversarial transformation networks
S. Baluja and I. Fischer · 2017
Cited alongside, same era.
Adversarial examples for semantic segmentation and object detection
C. Xie, J. Wang, Z. Zhang, Y. Zhou, and L. Xie an A. Yuille · 2017
Cited alongside, same era.
Mit saliency benchmark
Z. Bylinskii, T. Judd, A. Borji, L. Itti, F. Durand, A. Oliva, and A. Torralba
Cited in the paper.
Later among the works it cites.
Benchmarking neural network robustness to common corruptions and surface variations
D. Hendrycks and T. G. Dietterich · 2018
Later among the works it cites.
D. Su, H. Zhang, H. Chen, J. Yi, P.Y. Chen, and Y. Gao · 2018
Later among the works it cites.
Adversarial attacks beyond the image space
X. Zeng, C. Liu, Y. Wang, W. Qiu, L. Xie, Y. Tai, and A. Yuille · 2019
Closest in time.
Adversarial examples: Attacks and defenses for deep learning
X. Yuan, P. He, Q. Zhu, and X. Li · 2019
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Gazegan: Invariance analysis and a robust new model
Z. Che, A. Borji, G. Zhai, G. Guo, and P.L. Callet · 2019
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