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1. 论文信息
- 论文题目:End-to-end representation learning for Correlation Filter based tracking
- 论文出处:CVPR 2017
- 论文作者:Jack Valmadre,Luca Bertinetto等人
- 论文主页:http://www.robots.ox.ac.uk/~luca/cfnet.html
- 在线阅读:http://openaccess.thecvf.com/content_cvpr_2017/papers/Valmadre_End-To-End_Representation_Learning_CVPR_2017_paper.pdf
- 源码链接:https://github.com/bertinetto/cfnet
2. tracking部分实现过程
注意:
z分支正向传播并得到输出数据的代码如下所示:
net_z.eval({'exemplar', z_crop});
z_out_val_new = get_vars(net_z, z_out_id);
其中,get_vars是源码中定义的匿名函数:
get_vars = @(net, ids) cellfun(@(id) net.getVar(id).value, ids, 'UniformOutput', false);
这里的getVar函数,其用法为:
GETVAR - Get a copy of a layer definition
VAR = GETVAR(obj, NAME) returns a copy of the network variable with the specified NAME. NAME can also be a cell array of strings or an array of indexes. If no variable with a specified name or index exists, an error is thrown.See Also getVarIndex().
from http://www.vlfeat.org/matconvnet/mfiles/+dagnn/@DagNN/DagNN/#getvar-get-a-copy-of-a-layer-definition
对应的Visio文件在本人的网盘,链接:https://share.weiyun.com/58m46jE 密码:p101xr
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