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Dozens of new models on fixation prediction are published every year and compared on open benchmarks such as MIT300 and LSUN.
Treisman, A.M., Gelade, G.: A feature-integration theory of attention. Cognitive Psychology
1980
Earlier work this paper cites.
Koch, C., Ullman, S.: Shifts in selective visual attention: Towards the underlying neural circuitry. Human Neurobiology
1985
Earlier work this paper cites.
Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Machine Intell
1998
Earlier work this paper cites.
Li, Z.: A saliency map in primary visual cortex. Trends in Cognitive Sciences
2002
Earlier work this paper cites.
Jost, T., Ouerhani, N., Wartburg, R.v., Müri, R., Hügli, H.: Assessing the contribution of color in visual attention. Computer Vision and Image Understanding
2004
Earlier work this paper cites.
Tatler, B.W., Baddeley, R.J., Gilchrist, I.D.: Visual correlates of fixation selection: Effects of scale and time. Vision Research
2004
Earlier work this paper cites.
Itti, L.: Quantifying the contribution of low-level saliency to human eye movements in dynamic scenes. Visual Cognition
2005
Earlier work this paper cites.
Peters, R.J., Iyer, A., Itti, L., Koch, C.: Components of bottom-up gaze allocation in natural images. Vision Research
2005
Earlier work this paper cites.
Harel, J., Koch, C., Perona, P.: Graph-based visual saliency. In: Advances in neural information processing systems. pp. 545–552 (2006)
2006
Earlier work this paper cites.
Tatler, B.W.: The central fixation bias in scene viewing: Selecting an optimal viewing position independently of motor biases and image feature distributions. Journal of Vision
2007
Earlier work this paper cites.
Einhauser, W., Spain, M., Perona, P.: Objects predict fixations better than early saliency. Journal of Vision
2008
Earlier work this paper cites.
Tatler, B.W., Vincent, B.T.: Systematic tendencies in scene viewing. Journal of Eye Movement Research
2008
Earlier work this paper cites.
2008
Earlier work this paper cites.
Bruce, N.D.B., Tsotsos, J.K.: Saliency, attention, and visual search: An information theoretic approach. Journal of Vision
2009
Earlier work this paper cites.
Cerf, M., Harel, J., Huth, A., Einhäuser, W., Koch, C.: Decoding what people see from where they look: Predicting visual stimuli from scanpaths. In: Attention in Cognitive Systems, pp. 15–26. Springer Berlin Heidelberg (2009). https://doi.org/10.1007/978-3-642-00582-4_2,
2009
Earlier work this paper cites.
Judd, T., Ehinger, K., Durand, F., Torralba, A.: Learning to predict where humans look. In: 2009 IEEE 12th International Conference on Computer Vision. IEEE (Sep 2009). https://doi.org/10.1109/iccv.2009.5459462,
2009
Earlier work this paper cites.
Kienzle, W., Franz, M.O., Scholkopf, B., Wichmann, F.A.: Center-surround patterns emerge as optimal predictors for human saccade targets. Journal of Vision
2009
Earlier work this paper cites.
Vincent, B.T., Baddeley, R., Correani, A., Troscianko, T., Leonards, U.: Do we look at lights? using mixture modelling to distinguish between low- and high-level factors in natural image viewing. Visual Cognition
2009
Earlier work this paper cites.
Tatler, B.W., Hayhoe, M.M., Land, M.F., Ballard, D.H.: Eye guidance in natural vision: Reinterpreting salience. Journal of Vision
2011
Cited alongside, same era.
Wilming, N., Betz, T., Kietzmann, T.C., König, P.: Measures and limits of models of fixation selection. PLoS ONE
2011
Cited alongside, same era.
Borji, A., Itti, L.: State-of-the-art in visual attention modeling. IEEE Trans. Pattern Anal. Mach. Intell
2012
Cited alongside, same era.
Borji, A., Sihite, D.N., Itti, L.: Quantitative analysis of human-model agreement in visual saliency modeling: A comparative study. IEEE Trans. on Image Process
2012
Cited alongside, same era.
Judd, T., Durand, F.d., Torralba, A.: A Benchmark of Computational Models of Saliency to Predict Human Fixations. CSAIL Technical Reports (2012). https://doi.org/1721.1/68590
2012
Cited alongside, same era.
Xiao, J., Xu, P., Zhang, Y., Ehinger, K., Finkelstein, A., Kulkarni, S.: What can we learn from eye tracking data on 20,000 images? Journal of Vision
2015
Later among the works it cites.
Adeli, H., Vitu, F., Zelinsky, G.J.: A model of the superior colliculus predicts fixation locations during scene viewing and visual search. J. Neurosci
2016
Later among the works it cites.
Bruce, N.D.B., Catton, C., Janjic, S.: A deeper look at saliency: Feature contrast, semantics, and beyond. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE (Jun 2016). https://doi.org/10.1109/cvpr.2016.62,
2016
Later among the works it cites.
2016
Later among the works it cites.
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Le Meur, O., Baccino, T.: Methods for comparing scanpaths and saliency maps: Strengths and weaknesses. Behav Res
2012
Cited alongside, same era.
Barthelme, S., Trukenbrod, H., Engbert, R., Wichmann, F.: Modeling fixation locations using spatial point processes. Journal of Vision
2013
Cited alongside, same era.
Borji, A., Sihite, D.N., Itti, L.: Objects do not predict fixations better than early saliency: A re-analysis of einhauser et al.’s data. Journal of Vision
2013
Cited alongside, same era.
Riche, N., Duvinage, M., Mancas, M., Gosselin, B., Dutoit, T.: Saliency and human fixations: State-of-the-art and study of comparison metrics. In: 2013 IEEE International Conference on Computer Vision. IEEE (Dec 2013). https://doi.org/10.1109/iccv.2013.147,
2013
Cited alongside, same era.
Zhang, J., Sclaroff, S.: Saliency detection: A Boolean map approach. In: 2013 IEEE International Conference on Computer Vision. IEEE (Dec 2013). https://doi.org/10.1109/iccv.2013.26,
2013
Cited alongside, same era.
Itti, L., Borji, A.: Computational models: Bottom-up and top-down aspects. In: The Oxford Handbook of Attention. Oxford University Press (2014)
2014
Cited alongside, same era.
Koehler, K., Guo, F., Zhang, S., Eckstein, M.P.: What do saliency models predict? Journal of Vision
2014
Cited alongside, same era.
Bylinskii, Z., Recasens, A., Borji, A., Oliva, A., Torralba, A., Durand, F.: Where should saliency models look next? In: Computer Vision – ECCV 2016. pp. 809–824. Lecture Notes in Computer Science, Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46454-1_49,
2016
Later among the works it cites.
2016
Later among the works it cites.
Jetley, S., Murray, N., Vig, E.: End-to-end saliency mapping via probability distribution prediction. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE (Jun 2016). https://doi.org/10.1109/cvpr.2016.620,
2016
Later among the works it cites.
Riche, N.: Metrics for saliency model validation. In: From Human Attention to Computational Attention, pp. 209–225. Springer New York (2016). https://doi.org/10.1007/978-1-4939-3435-5_12,
2016
Later among the works it cites.
Riche, N.: Saliency model evaluation. In: From Human Attention to Computational Attention, pp. 245–267. Springer New York (2016). https://doi.org/10.1007/978-1-4939-3435-5_14,
2016
Later among the works it cites.
Rothkopf, C.A., Ballard, D.H., Hayhoe, M.M.: Task and context determine where you look. Journal of Vision
2016
Later among the works it cites.
Thomas, C.: OpenSalicon: An open source implementation of the salicon saliency model. CoRR
2016
Later among the works it cites.
Kruthiventi, S.S.S., Ayush, K., Babu, R.V.: DeepFix: A fully convolutional neural network for predicting human eye fixations. IEEE Trans. on Image Process
2017
Closest in time.
Kümmerer, M., Wallis, T.S.A., Gatys, L.A., Bethge, M.: Understanding low- and high-level contributions to fixation prediction. In: The IEEE International Conference on Computer Vision (ICCV). IEEE (Oct 2017)
2017
Closest in time.
Nuthmann, A., Einhäuser, W., Schütz, I.: How well can saliency models predict fixation selection in scenes beyond central bias? a new approach to model evaluation using generalized linear mixed models. Front. Hum. Neurosci
2017
Closest in time.
2017
Closest in time.
Schütt, H.H., Rothkegel, L.O.M., Trukenbrod, H.A., Reich, S., Wichmann, F.A., Engbert, R.: Likelihood-based parameter estimation and comparison of dynamical cognitive models. Psychological Review
2017
Closest in time.
Yu, F., Kontschieder, P., Song, S., Jiang, M., Zhang, Y., Zhao, C.Q., Funkhouser, T., Xiao, J.: Large-scale scene understanding challenge. http://http://lsun.cs.princeton.edu/2017/
2017
Closest in time.
Yu, F., Kontschieder, P., Song, S., Jiang, M., Zhang, Y., Zhao, C.Q., Funkhouser, T., Xiao, J.: SALICON saliency prediction challenge. http://salicon.net/challenge-2017/
2017
Closest in time.