| Salicon: Saliency in context M Jiang, S Huang, J Duan, Q Zhao Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 695 | 2015 |
| Salicon: Reducing the semantic gap in saliency prediction by adapting deep neural networks X Huang, C Shen, X Boix, Q Zhao Proceedings of the IEEE international conference on computer vision, 262-270, 2015 | 617 | 2015 |
| Atypical visual saliency in autism spectrum disorder quantified through model-based eye tracking S Wang, M Jiang, XM Duchesne, EA Laugeson, DP Kennedy, R Adolphs, ... Neuron 88 (3), 604-616, 2015 | 375 | 2015 |
| Co-tracking using semi-supervised support vector machines F Tang, S Brennan, Q Zhao, H Tao 2007 IEEE 11th International Conference on Computer Vision, 1-8, 2007 | 348 | 2007 |
| Learning a saliency map using fixated locations in natural scenes Q Zhao, C Koch Journal of vision 11 (3), 9-9, 2011 | 319 | 2011 |
| Predicting human gaze beyond pixels J Xu, M Jiang, S Wang, MS Kankanhalli, Q Zhao Journal of vision 14 (1), 28-28, 2014 | 312 | 2014 |
| Learning to learn from noisy labeled data J Li, Y Wong, Q Zhao, MS Kankanhalli Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 302 | 2019 |
| A closed-form solution to retinex with nonlocal texture constraints Q Zhao, P Tan, Q Dai, L Shen, E Wu, S Lin IEEE transactions on pattern analysis and machine intelligence 34 (7), 1437-1444, 2012 | 198 | 2012 |
| Probabilistic graphlet transfer for photo cropping L Zhang, M Song, Q Zhao, X Liu, J Bu, C Chen IEEE Transactions on Image Processing 22 (2), 802-815, 2012 | 188 | 2012 |
| Foveation-based mechanisms alleviate adversarial examples Y Luo, X Boix, G Roig, T Poggio, Q Zhao arXiv preprint arXiv:1511.06292, 2015 | 180 | 2015 |
| Emotional attention: A study of image sentiment and visual attention S Fan, Z Shen, M Jiang, BL Koenig, J Xu, MS Kankanhalli, Q Zhao Proceedings of the IEEE Conference on computer vision and pattern …, 2018 | 136 | 2018 |
| Differential earth mover's distance with its applications to visual tracking Q Zhao, Z Yang, H Tao IEEE Transactions on Pattern Analysis and Machine Intelligence 32 (2), 274-287, 2008 | 136 | 2008 |
| Learning saliency-based visual attention: A review Q Zhao, C Koch Signal Processing 93 (6), 1401-1407, 2013 | 132 | 2013 |
| Weakly supervised photo cropping L Zhang, M Song, Y Yang, Q Zhao, C Zhao, N Sebe IEEE Transactions on Multimedia 16 (1), 94-107, 2013 | 129 | 2013 |
| Webpage saliency C Shen, Q Zhao Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014 | 126 | 2014 |
| Learning to detect human-object interactions with knowledge B Xu, Y Wong, J Li, Q Zhao, MS Kankanhalli Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 121 | 2019 |
| Estimation of intrinsic image sequences from image+ depth video KJ Lee, Q Zhao, X Tong, M Gong, S Izadi, SU Lee, P Tan, S Lin Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 121 | 2012 |
| Learning visual attention to identify people with autism spectrum disorder M Jiang, Q Zhao Proceedings of the ieee international conference on computer vision, 3267-3276, 2017 | 117 | 2017 |
| Learning visual saliency by combining feature maps in a nonlinear manner using AdaBoost Q Zhao, C Koch Journal of Vision 12 (6), 22-22, 2012 | 113 | 2012 |
| Object tracking using color correlogram Q Zhao, H Tao 2005 IEEE International Workshop on Visual Surveillance and Performance …, 2005 | 109 | 2005 |
