Unsupervised Learning of Spatiotemporally Coherent Metrics Note here: it's a learning note on the topic of unsupervised learning on videos, a novel work published by Yann LeCun's group. Link: http://arxiv.org/pdf/1412.6056.pdf Motivation: Temporal co…
Unsupervised Learning of Visual Representations using Videos Note here: it's a learning note on Prof. Gupta's novel work published on ICCV2015. It's really exciting to know how unsupervised learning method can contribute to learn visual representatio…
Unsupervised Visual Representation Learning by Context Prediction Note here: it's a learning note on unsupervised learning model from Prof. Gupta's group. Link: http://120.52.73.9/www.cv-foundation.org/openaccess/content_iccv_2015/papers/Doersch_Unsu…
[论文标题]CoupledCF: Learning Explicit and Implicit User-item Couplings in Recommendation for Deep Collaborative Filtering  (IJCAI-2018 ) [论文作者]Quangui Zhang, Longbing Cao,Chengzhang Zhu,Zhiqiang Li,Jinguang Sun [论文链接]Paper (7-pages // Double column) [摘要…
[论文标题]List-wise learning to rank with matrix factorization for collaborative filtering   (RecSys '10 recsys.ACM ) [论文作者] Yue ShiDelft University of Technology, Delft, Netherlands Martha LarsonDelft University of Technology, Delft, Netherlands Alan Ha…
[论文标题]Deep Learning based Recommender System: A Survey and New Perspectives ( ACM Computing Surveys · July 2017) [论文作者] SHUAI ZHANG, University of New South WalesLINA YAO, University of New South WalesAIXIN SUN, Nanyang Technological UniversityYI TAY…
Introduction (1)IVPR问题: 根据一张图片从视频中识别出行人的方法称为 image to video person re-id(IVPR) 应用: ① 通过嫌犯照片,从视频中识别出嫌犯: ② 通过照片,寻找走失人口. (2)图片-视频行人匹配问题的描述: (3)IVPR的难点: ① 图像.视频的特征不同:视频包含视觉外貌特征(visual appearance features)和时空特征(spatial-temporal features),而图片只包含视觉外貌特征: ② I…
http://blog.csdn.net/zouxy09/article/details/8775360 一.概述 Artificial Intelligence,也就是人工智能,就像长生不老和星际漫游一样,是人类最美好的梦想之一.虽然计算机技术已经取得了长足的进步,但是到目前为止,还没有一台电脑能产生“自我”的意识.是的,在人类和大量现成数据的帮助下,电脑可以表现的十分强大,但是离开了这两者,它甚至都不能分辨一个喵星人和一个汪星人. 图灵(图灵,大家都知道吧.计算机和人工智能的鼻祖,分别对应于…
十.总结与展望 1)Deep learning总结 深度学习是关于自动学习要建模的数据的潜在(隐含)分布的多层(复杂)表达的算法.换句话来说,深度学习算法自动的提取分类需要的低层次或者高层次特征. 高层次特征,一是指该特征可以分级(层次)地依赖其他特征,例如:对于机器视觉,深度学习算法从原始图像去学习得到它的一个低层次表达,例如边缘检测器, 小波滤波器等,然后在这些低层次表达的基础上再建立表达,例如这些低层次表达的线性或者非线性组合,然后重复这个过程,最后得到一个高层次的表达. Deep lea…
Describing Videos by Exploiting Temporal Structure Note here: it's a learning note on the topic of video representations. Link: http://120.52.73.75/arxiv.org/pdf/1502.08029.pdf Motivation: They argue that there are two categories of temporal structur…