王兴刚
教授
所属大学: 华中科技大学
所属学院: 电子信息与通信学院
个人简介
教育经历 2005.9 - 2009.6 华中科技大学 - 本科 (学士) 2009.9 - 2014.12 华中科技大学 - 研究生 (博士) 毕业
研究领域
计算机视觉,机器学习,深度学习,尤其在于数据受限和计算受限情况下的视觉识别。
近期论文
Wang,Xinggang,Wang,Xinggang,Latecki,Jan,Longin,Liu,Wenyu,Bai,Xiang.Wang,Xinggang.Feature Context for Image Classification and Object Detection.2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2011, Wang,Xinggang,Wang,Xinggang,Latecki,Jan,Longin,Liu,Wenyu,Yang,Xingwei,Bai,Xiang.Wang,Xinggang.Maximal Cliques that Satisfy Hard Constraints with Application to Deformable Object Model Learning.Advances in Neural Information Processing Systems 24 (NIPS 2011),2011, Wang,Xinggang,Wang,Xinggang,Latecki,Jan,Longin,Liu,Wenyu,Ma,Tianyang,Bai,Xiang.Wang,Xinggang.Fan Shape Model for Object Detection.2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2012, Wang,Xinggang,Wang,Xinggang,Wang,Tu,Zhuowen,Liu,Wenyu,Bai,Xiang,Wang,Baoyuan.Wang,Xinggang.Max-margin multiple-instance dictionary learning.International Conference on Machine Learning (ICML), Atlanta, June, 2013,2013, Wang,Xinggang,Latecki,Jan,Longin,Liu,Wenyu,Bai,Xiang.Feng,Bin.Bag of contour fragments for robust shape classification.Pattern Recognition,2014, Shen,Wei,Zhang,Zhijiang,Yan,Wang,Xinggang.Bai,Xiang.DeepContour: A deep convolutional feature learned by positive-sharing loss for contour detection.2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2015, Zhu,Zhuotun,Wang,Xinggang,Yao,Cong.Bai,Xiang.Relaxed Multiple-Instance SVM with Application to Object Discovery.2015 IEEE International Conference on Computer Vision (ICCV),2015, Tang,Peng,Bai,Xiang,Wang,Xinggang.Liu,Wenyu.Multiple Instance Detection Network with Online Instance Classifier Refinement.2017 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),2017, Wang,Xinggang,Wang,Xinggang,Liu,Wenyu,Tang,Peng,Yan,Yongluan.Wang,Xinggang,Bai,Xiang.Revisiting multiple instance neural networks.Pattern Recognition,2017, Huang,Zilong,Wang,Jingdong,Liu,Wenyu,Wang,Jiasi.Wang,Wang,Xinggang.Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing.2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),2018,