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Visual saliency models have enjoyed a big leap in performance in recent years, thanks to advances in deep learning and large scale annotated data.
A. M. Treisman and G. Gelade, “A feature-integration theory of attention,”
1980
Earlier work this paper cites.
C. Koch and S. Ullman, “Shifts in selective visual attention: towards the underlying neural circuitry,”
1985
Earlier work this paper cites.
C. Koch and S. Ullman, “Shifts in selective visual attention: towards the underlying neural circuitry,” in
1987
Earlier work this paper cites.
L. Itti, C. Koch, and E. Niebur, “A model of saliency-based visual attention for rapid scene analysis,”
1998
Earlier work this paper cites.
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, “Gradient-based learning applied to document recognition,” in
1998
Earlier work this paper cites.
Y. Rubner, C. Tomasi, and L. J. Guibas, “The earth mover’s distance as a metric for image retrieval,”
2000
Earlier work this paper cites.
L. Itti and C. Koch, “Computational modelling of visual attention,”
2001
Earlier work this paper cites.
D. Parkhurst, K. Law, and E. Niebur, “Modeling the role of salience in the allocation of overt visual attention,”
2002
Earlier work this paper cites.
M. M. Hayhoe and D. H. Ballard, “Eye movements in natural behavior,”
2005
Earlier work this paper cites.
N. Bruce and J. Tsotsos, “Saliency based on information maximization,” in
2005
Earlier work this paper cites.
R. J. Peters, A. Iyer, L. Itti, and C. Koch, “Components of bottom-up gaze allocation in natural images,”
2005
Earlier work this paper cites.
H. F. Chua, J. E. Boland, and R. E. Nisbett, “Cultural variation in eye movements during scene perception,”
2005
Earlier work this paper cites.
J. Harel, C. Koch, and P. Perona, “Graph-based visual saliency,” in
2006
Earlier work this paper cites.
G.-B. Huang, Q.-Y. Zhu, and C.-K. Siew, “Extreme learning machine: theory and applications,”
2006
Earlier work this paper cites.
X. Hou and L. Zhang, “Saliency detection: A spectral residual approach,” in
2007
Earlier work this paper cites.
B. W. Tatler, “The central fixation bias in scene viewing: Selecting an optimal viewing position independently of motor biases and image feature distributions,”
2007
Earlier work this paper cites.
G. B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller, “Labeled faces in the wild: A database for studying face recognition in unconstrained environments,” Technical Report 07-49, University of Massachusetts, Amherst, Tech. Rep., 2007
2007
Earlier work this paper cites.
L. Zhang, M. H. Tong, T. K. Marks, H. Shan, and G. W. Cottrell, “Sun: A bayesian framework for saliency using natural statistics,”
2008
Earlier work this paper cites.
C. Guo, Q. Ma, and L. Zhang, “Spatio-temporal saliency detection using phase spectrum of quaternion fourier transform,” in
2008
Earlier work this paper cites.
L. Elazary and L. Itti, “Interesting objects are visually salient,”
2008
Earlier work this paper cites.
W. Einhäuser, M. Spain, and P. Perona, “Objects predict fixations better than early saliency,”
2008
Earlier work this paper cites.
T. Judd, K. Ehinger, F. Durand, and A. Torralba, “Learning to predict where humans look,” in
2009
Earlier work this paper cites.
M. Cerf, E. P. Frady, and C. Koch, “Faces and text attract gaze independent of the task: Experimental data and computer model,”
2009
Earlier work this paper cites.
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, “Imagenet: A large-scale hierarchical image database,” in
2009
Earlier work this paper cites.
T. Judd, K. Ehinger, F. Durand, and A. Torralba, “Learning to predict where humans look.” in
2009
Earlier work this paper cites.
M. Cerf, E. P. Frady, and C. Koch, “Faces and text attract gaze independent of the task: Experimental data and computer model,”
2009
Earlier work this paper cites.
S. Ramanathan, H. Katti, N. Sebe, M. Kankanhalli, and T.-S. Chua, “An eye fixation database for saliency detection in images,”
2010
Earlier work this paper cites.
A. Nuthmann and J. M. Henderson, “Object-based attentional selection in scene viewing,”
2010
Earlier work this paper cites.
B. Schauerte, J. Richarz, and G. A. Fink, “Saliency-based identification and recognition of pointed-at objects,” in
2010
Earlier work this paper cites.
T. Foulsham, J. T. Cheng, J. L. Tracy, J. Henrich, and A. Kingstone, “Gaze allocation in a dynamic situation: Effects of social status and speaking,”
2010
Earlier work this paper cites.
P. K. Mital, T. J. Smith, R. L. Hill, and J. M. Henderson, “Clustering of gaze during dynamic scene viewing is predicted by motion,”
2011
Earlier work this paper cites.
M. Spain and P. Perona, “Measuring and predicting object importance,”
2011
Earlier work this paper cites.
G. Kootstra, B. de Boer, and L. R. Schomaker, “Predicting eye fixations on complex visual stimuli using local symmetry,”
2011
Earlier work this paper cites.
T. Judd, F. Durand, and A. Torralba, “Fixations on low-resolution images,”
2011
Earlier work this paper cites.
S. Oh, A. Hoogs, A. Perera, N. Cuntoor, C.-C. Chen, J. T. Lee, S. Mukherjee, J. Aggarwal, H. Lee, L. Davis
2011
Earlier work this paper cites.
A. Borji, D. N. Sihite, and L. Itti, “Salient object detection: A benchmark,” in
2012
Earlier work this paper cites.
A. Borji, D. N. Sihite, and L. Itti, “Probabilistic learning of task-specific visual attention,” in
2012
Earlier work this paper cites.
A. Garcia-Diaz, X. R. Fdez-Vidal, X. M. Pardo, and R. Dosil, “Saliency from hierarchical adaptation through decorrelation and variance normalization,”
2012
Earlier work this paper cites.
A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in
2012
Earlier work this paper cites.
A. Borji, “Boosting bottom-up and top-down visual features for saliency estimation,” in
2012
Earlier work this paper cites.
J. Shen and L. Itti, “Top-down influences on visual attention during listening are modulated by observer sex,”
2012
Earlier work this paper cites.
D. Rudoy, D. B. Goldman, E. Shechtman, and L. Zelnik-Manor, “Crowdsourcing gaze data collection,”
2012
Earlier work this paper cites.
2012
Earlier work this paper cites.
H. Pirsiavash and D. Ramanan, “Detecting activities of daily living in first-person camera views,” in
2012
Earlier work this paper cites.
H. Hadizadeh, M. J. Enriquez, and I. V. Bajic, “Eye-tracking database for a set of standard video sequences,”
2012
Earlier work this paper cites.
A. Borji and L. Itti, “State-of-the-art in visual attention modeling,”
2013
Earlier work this paper cites.
A. Borji, D. N. Sihite, and L. Itti, “Quantitative analysis of human-model agreement in visual saliency modeling: A comparative study,”
2013
Earlier work this paper cites.
——, “What stands out in a scene? a study of human explicit saliency judgment,”
2013
Earlier work this paper cites.
A. Borji, H. R. Tavakoli, D. N. Sihite, and L. Itti, “Analysis of scores, datasets, and models in visual saliency prediction,” in
2013
Earlier work this paper cites.
S. Winkler and R. Subramanian, “Overview of eye tracking datasets,” in
2013
Earlier work this paper cites.
J. Zhang and S. Sclaroff, “Saliency detection: A boolean map approach,” in
2013
Earlier work this paper cites.
D. Rudoy, D. B. Goldman, E. Shechtman, and L. Zelnik-Manor, “Learning video saliency from human gaze using candidate selection,” in
2013
Earlier work this paper cites.
T. V. Nguyen, M. Xu, G. Gao, M. Kankanhalli, Q. Tian, and S. Yan, “Static saliency vs. dynamic saliency: a comparative study,” in
2013
Cited alongside, same era.
B. M’t Hart, H. C. Schmidt, C. Roth, and W. Einhäuser, “Fixations on objects in natural scenes: dissociating importance from salience,”
2013
Cited alongside, same era.
A. Borji, D. N. Sihite, and L. Itti, “Objects do not predict fixations better than early saliency: A re-analysis of einhaeuser et al.’s data,”
2013
Cited alongside, same era.
C. Kim and P. Milanfar, “Visual saliency in noisy images,”
2013
Cited alongside, same era.
L. C. Zitnick and D. Parikh, “Bringing semantics into focus using visual abstraction,” in
2013
Cited alongside, same era.
A. Belardinelli, M. Y. Stepper, and M. V. Butz, “It’s in the eyes: Planning precise manual actions before execution,”
2016
Later among the works it cites.
2016
Later among the works it cites.
J. Wang, A. Borji, C.-C. J. Kuo, and L. Itti, “Learning a combined model of visual saliency for fixation prediction,”
2016
Later among the works it cites.
J. Lu, J. Yang, D. Batra, and D. Parikh, “Hierarchical question-image co-attention for visual question answering,” in
2016
Later among the works it cites.
H. R. Tavakoli, F. Ahmed, A. Borji, and J. Laaksonen, “Saliency revisited: Analysis of mouse movements versus fixations,”
2017
Later among the works it cites.
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K. Yun, Y. Peng, D. Samaras, G. J. Zelinsky, and T. L. Berg, “Studying relationships between human gaze, description, and computer vision,” in
2013
Cited alongside, same era.
A. Borji, D. N. Sihite, and L. Itti, “What/where to look next? modeling top-down visual attention in complex interactive environments,”
2014
Cited alongside, same era.
K. Koehler, F. Guo, S. Zhang, and M. P. Eckstein, “What do saliency models predict?”
2014
Cited alongside, same era.
M. Jiang, J. Xu, and Q. Zhao, “Saliency in crowd,” in
2014
Cited alongside, same era.
C. Shen and Q. Zhao, “Webpage saliency,” in
2014
Cited alongside, same era.
A. Coutrot and N. Guyader, “How saliency, faces, and sound influence gaze in dynamic social scenes,”
2014
Cited alongside, same era.
Z. Bylinskii, T. Judd, A. Borji, L. Itti, F. Durand, A. Oliva, and A. Torralba, “Mit saliency benchmark,” 2014
2014
Cited alongside, same era.
2017
Later among the works it cites.
2017
Later among the works it cites.
Y. Liu, S. Zhang, M. Xu, and X. He, “Predicting salient face in multipleface videos,” in
2017
Later among the works it cites.
M. Assens, X. Giro-i Nieto, K. McGuinness, and N. E. O’Connor, “Saltinet: Scan-path prediction on 360 degree images using saliency volumes,” in
2017
Later among the works it cites.
V. Leboran, A. Garcia-Diaz, X. R. Fdez-Vidal, and X. M. Pardo, “Dynamic whitening saliency,”
2017
Later among the works it cites.
M. Xu, L. Jiang, X. Sun, Z. Ye, and Z. Wang, “Learning to detect video saliency with hevc features,”
2017
Later among the works it cites.
M. Kümmerer, T. S. Wallis, L. A. Gatys, and M. Bethge, “Understanding low-and high-level contributions to fixation prediction,” in
2017
Later among the works it cites.
S. S. Kruthiventi, K. Ayush, and R. V. Babu, “Deepfix: A fully convolutional neural network for predicting human eye fixations,”
2017
Later among the works it cites.
2017
Later among the works it cites.
H. R. Tavakoli, A. Borji, J. Laaksonen, and E. Rahtu, “Exploiting inter-image similarity and ensemble of extreme learners for fixation prediction using deep features,”
2017
Later among the works it cites.
W. Wang and J. Shen, “Deep visual attention prediction,”
2017
Later among the works it cites.
S. Gorji and J. J. Clark, “Attentional push: A deep convolutional network for augmenting image salience with shared attention modeling in social scenes,” in
2017
Later among the works it cites.
X. Sun, Z. Huang, H. Yin, and H. T. Shen, “An integrated model for effective saliency prediction.” in
2017
Later among the works it cites.
2017
Later among the works it cites.
Y. Xu, J. Wu, N. Li, S. Gao, and J. Yu, “Personalized saliency and its prediction,”
2017
Later among the works it cites.
2017
Later among the works it cites.
G. Leifman, D. Rudoy, T. Swedish, E. Bayro-Corrochano, and R. Raskar, “Learning gaze transitions from depth to improve video saliency estimation,” in
2017
Later among the works it cites.
D. Zanca and M. Gori, “Variational laws of visual attention for dynamic scenes,” in
2017
Later among the works it cites.
J. M. Wolfe and T. S. Horowitz, “Five factors that guide attention in visual search,”
2017
Later among the works it cites.
2017
Later among the works it cites.
C. Sun, A. Shrivastava, S. Singh, and A. Gupta, “Revisiting unreasonable effectiveness of data in deep learning era,” in
2017
Later among the works it cites.
I. Schwartz, A. Schwing, and T. Hazan, “High-order attention models for visual question answering,” in
2017
Later among the works it cites.
M. Jiang and Q. Zhao, “Learning visual attention to identify people with autism spectrum disorder,” in
2017
Later among the works it cites.
2017
Later among the works it cites.
Z. Bylinskii, T. Judd, A. Oliva, A. Torralba, and F. Durand, “What do different evaluation metrics tell us about saliency models?”
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Q. Zheng, J. Jiao, Y. Cao, and R. W. Lau, “Task-driven webpage saliency,” in
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S. Fan, Z. Shen, M. Jiang, B. L. Koenig, J. Xu, M. S. Kankanhalli, and Q. Zhao, “Emotional attention: A study of image sentiment and visual attention,” in
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W. Wang, J. Shen, F. Guo, M.-M. Cheng, and A. Borji, “Revisiting video saliency: A large-scale benchmark and a new model,” in
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L. Jiang, M. Xu, T. Liu, M. Qiao, and Z. Wang, “Deepvs: A deep learning based video saliency prediction approach,” in
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Z. Zhang, Y. Xu, J. Yu, and S. Gao, “Saliency detection in 360° videos,” in
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S. Jia, “Eml-net: An expandable multi-layer network for saliency prediction,”
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S. F. Dodge and L. J. Karam, “Visual saliency prediction using a mixture of deep neural networks,”
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C. Wloka, I. Kotseruba, and J. K. Tsotsos, “Active fixation control to predict saccade sequences,” in
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C. Bak, A. Kocak, E. Erdem, and A. Erdem, “Spatio-temporal saliency networks for dynamic saliency prediction,”
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S. Gorji and J. J. Clark, “Going from image to video saliency: Augmenting image salience with dynamic attentional push,” in
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M. Sun, Z. Zhou, Q. Hu, Z. Wang, and J. Jiang, “Sg-fcn: A motion and memory-based deep learning model for video saliency detection,”
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M. Kummerer, T. S. Wallis, and M. Bethge, “Saliency benchmarking made easy: Separating models, maps and metrics,” in
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W. Wang, J. Shen, and L. Shao, “Video salient object detection via fully convolutional networks,”
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J. M. Henderson and T. R. Hayes, “Meaning guides attention in real-world scene images: Evidence from eye movements and meaning maps,”
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Z. che, A. Borji, G. Zhai, and X. Min, “Invariance analysis of saliency models versus human gaze during scene free viewing,”
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