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李甲 ( 教授 ) 赞
的个人主页 http://shi.buaa.edu.cn/cvteam/zh_CN/index.htm
教授博士生导师硕士生导师
主要任职：博士生导师，硕士生导师

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[31] .Jia Li, Yonghong Tian*, Tiejun Huang and Wen Gao. Probabilistic Multi-Task Learning for Visual Saliency Estimation in Video. International Journal of Computer Vision, 90(2), pp. 150-165, 2010. (CCF-A)
[32] .Jia Li, Dong Xu* and Wen Gao. Removing Label Ambiguity in Learning-Based Visual Saliency Estimation. IEEE Transactions on Image Processing, 21(4), pp. 1513 - 1525, 2012. (CCF-A)
[33] .Jia Li*, Yonghong Tian* and Tiejun Huang. Visual Saliency with Statistical Priors. International Journal of Computer Vision, 107(3), pp.239-253, 2014. (CCF-A)
[34] .Yonghong Tian*, Jia Li*, Shui Yu and Tiejun Huang. Learning Complementary Saliency Priors for Foreground Object Segmentation in Complex Scenes. International Journal of Computer Vision, 111(2), pp.153-170, 2015. (CCF-A)
[35] .Jia Li, Ling-Yu Duan*, Xiaowu Chen, Tiejun Huang and Yonghong Tian. Finding the Secret of Image Saliency in the Frequency Domain. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(12), pp. 2428-2440, 2015. (CCF-A)
[36] .Ali Borji#, Mingming Cheng#*, Huaizu Jiang and Jia Li. Salient Object Detection: A Benchmark. IEEE Transactions on Image Processing, 24(12), pp. 5706-5722, 2015. (CCF-A)
[37] .Jia Li*, Yonghong Tian*, Xiaowu Chen and Tiejun Huang. Measuring Visual Surprise Jointly from Intrinsic and Extrinsic Contexts for Image Saliency Estimation. International Journal of Computer Vision, 120, 44-60, 2016. (CCF-A)
[38] .Jia Li*, Changqun Xia and Xiaowu Chen*, A Benchmark Dataset and Saliency-guided Stacked Autoencoders for Video-based Salient Object Detection. IEEE Transactions on Image Processing. 27(1), pp. 349-364, 2018. (CCF-A)
[39] .Yu Zhang, Xiaowu Chen*, Jia Li, Chen Wang, Changqun Xia and Jun Li. Semantic Object Segmentation in Tagged Videos via Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(7), 1741-1754, July 2018. (CCF-A)
[40] .Yu Zhang*, Xiaowu Chen, Jia Li, Wei Teng and Haokun Song. Exploring Weakly Labeled Images for Video Object Segmentation with Submodular Proposal Selection. IEEE Transactions on Image Processing, 27(9), pp. 4245-4259, Sept. 2018. (CCF-A)

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