Dataset: MSRA A&B are introduced in this paper. A conditional Random Field based method was proposed as where with K features contributing to the first term and a pairwise features being the second. The pairwise is learning-free. a_x is the label of…
<Salient Object Detection: A Survey>作者:Ali Borji.Ming-Ming Cheng.Huaizu Jiang and Jia Li 基本按照文章中文献出现的顺序. 一.L. Itti, C. Koch, and E. Niebur, “A model of saliency-based visual attention for rapid scene analysis,” IEEE TPAMI, 1998. 一个用于快速场景分析的基于显著性的视觉注…
Learning Dynamic Memory Networks for Object Tracking ECCV 2018Updated on 2018-08-05 16:36:30 Paper: arXiv version Code: https://github.com/skyoung/MemTrack (Tensorflow Implementation) [Note]This paper is developed based on Siamese Network and DNC(Na…
MetaAnchor: Learning to Detect Objects with Customized Anchors Intro 本文我其实看了几遍也没看懂,看了meta以为是一个很高大上的东西,一搜是元学习的范畴,学会如何学习,很绕人.万般无奈之下请教了下老师,才知道他想表达什么.其实作者的想法很简单,就是先把最后anchor预测类别和位置的权重拿出来,这里的权重通过设计另一个网络来预测,而这个网络的参数又可以通过整个网络的训练梯度回传来学习.这样做的好处是,将anchor的配置(w,…
1. 早期C. Koch与S. Ullman的研究工作. 他们提出了非常有影响力的生物启发模型. C. Koch and S. Ullman . Shifts in selective visual attention: Towards the underlying neural circuitry. Human Neurobiology, 4(4):219-227, 1985. C. Koch and T. Poggio. Predicting the Visual World: Silenc…
这篇blog,原来是西弗吉利亚大学的Li xin整理的,CV代码相当的全,不知道要经过多长时间的积累才会有这么丰富的资源,在此谢谢LI Xin .我现在分享给大家,希望可以共同进步!还有,我需要说一下,不管你的理论有多么漂亮,不管你有多聪明,如果没有实验来证明,那么都是错误的. OK~本博文未经允许,禁止转载哦! By wei shen Reproducible Research in Computational Science “It doesn't matter how beautif…
Awesome Object Detection 2018-08-10 09:30:40 This blog is copied from: https://github.com/amusi/awesome-object-detection This is a list of awesome articles about object detection. R-CNN Fast R-CNN Faster R-CNN Light-Head R-CNN Cascade R-CNN SPP-Net Y…
CVPR2015 Papers震撼来袭! CVPR 2015的文章可以下载了,如果链接无法下载,可以在Google上通过搜索paper名字下载(友情提示:可以使用filetype:pdf命令). Going Deeper With ConvolutionsChristian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke…
此部分是计算机视觉部分,主要侧重在底层特征提取,视频分析,跟踪,目标检测和识别方面等方面.对于自己不太熟悉的领域比如摄像机标定和立体视觉,仅仅列出上google上引用次数比较多的文献.有一些刚刚出版的文章,个人非常喜欢,也列出来了. 33. SIFT关于SIFT,实在不需要介绍太多,一万多次的引用已经说明问题了.SURF和PCA-SIFT也是属于这个系列.后面列出了几篇跟SIFT有关的问题.[1999 ICCV] Object recognition from local scale-invar…
From: http://www.pamitc.org/cvpr15/program.php Official Program for CVPR 2015 Monday, June 8 8:30am-8:40am Ballrooms A,B,C Rooms 302,304,306 Opening Remarks from Conference Chairs The opening remarks will be made from Ballrooms A,B,C, but a live vid…
my paper~~ 1.(DAP,IAP)Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer 2.(ALE)Label-Embedding for Attribute-Based Classification 3.(SAE)Semantic Autoencoder for Zero-shot Learning CVPR2017 https://github.com/waitwait…
My deep learning reading list 主要是顺着Bengio的PAMI review的文章找出来的.包括几本综述文章,将近100篇论文,各位山头们的Presentation.全部都可以在google上找到.BTW:由于我对视觉尤其是检测识别比较感兴趣,所以关于DL的应用主要都是跟Vision相关的.在其他方面比如语音或者NLP,很少或者几乎没有.个人非常看好CNN和Sparse Autoencoder,这个list也反映了我的偏好,仅供参考. Review Book Lis…
CVPR2017 paper list Machine Learning 1 Spotlight 1-1A Exclusivity-Consistency Regularized Multi-View Subspace Clustering Xiaojie Guo, Xiaobo Wang, Zhen Lei, Changqing Zhang, Stan Z. Li Borrowing Treasures From the Wealthy: Deep Transfer Learning Thro…
目录 原文链接:小样本学习与智能前沿 01 Transforming Samples from Dtrain 02 Transforming Samples from a Weakly Labeled or Unlabeled Data Set 03 Transforming Samples from Similar Data Sets Discussion and Summary 原文链接:小样本学习与智能前沿 上一篇:A Survey on Few-Shot Learning | Intro…
Deep Learning in a Nutshell: Core Concepts This post is the first in a series I’ll be writing for Parallel Forall that aims to provide an intuitive and gentle introduction todeep learning. It covers the most important deep learning concepts and aims…
Deep Learning in a Nutshell: Core Concepts Share: Posted on November 3, 2015by Tim Dettmers 7 CommentsTagged cuDNN, Deep Learning, Deep Neural Networks, Machine Learning,Neural Networks This post is the first in a series I’ll be writing for Paral…
