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AIR学术沙龙第36期|人工智能医疗保健和虚拟世界的可穿戴传感器和触觉技术
先立后破?实现双碳目标
迎接生物药制造的第四次浪潮-
支撑未来海量资源接入,电力系统通用信息模型(CIM)发展探讨
报告题目:
『清华信息大讲堂』第 78 讲:基于稀疏表达的图像重建与人脸识别
 报告人:
张磊
香港理工大学
报告时间:
2011-09-15 15:00
报告地点:
中央主楼511
主办单位:
信息学院
  简介:

摘要:

    This talk will introduce some of our recent research progress in sparse representation based image reconstruction and face recognition. For image reconstruction, we will first introduce the adaptive sparse domain selection and regularization scheme, and then present the centralized sparse representation (CSR) model we recently developed. The CSR is very simple but very powerful, and it shows state-of-the-art results in image denoising, deblurring and super-resolution.
    Apart from image reconstruction, sparse representation has also been attracting lots of attention in face recognition, and it has shown many interesting results.  However, is it really the sparsity that helps face recognition? In this talk, we will demonstrate that it is not the sparse representation, but the collaborative representation, that truly helps face recognition.
 
 
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