登录
首页 » matlab » mvcnn-master

mvcnn-master

于 2020-12-04 发布
0 93
下载积分: 1 下载次数: 1

代码说明:

说明:  计算机视觉中一个长期存在的问题是关于用于识别的三维形状的表示:三维形状是否应该使用操作在其原生三维格式(如体素网格或多边形网格)上的描述符来表示,还是可以使用基于视图的描述符来有效地表示?我们在学习从一组二维图像上呈现的视图中识别三维图形的背景下解决了这个问题。我们首先介绍了一个经过训练的标准CNN架构,可以独立地识别呈现在视图中的形状,并展示了一个3D形状甚至可以从中识别出来(A longstanding question in computer vision concerns the representation of 3D shapes for recognition: should 3D shapes be represented with descriptors operating on their native 3D formats)

文件列表:

mvcnn-master, 0 , 2019-01-04
mvcnn-master\.gitignore, 4 , 2019-01-04
mvcnn-master\.gitmodules, 222 , 2019-01-04
mvcnn-master\LICENCE, 1074 , 2019-01-04
mvcnn-master\README.md, 4408 , 2019-01-04
mvcnn-master\caffe, 0 , 2019-01-04
mvcnn-master\caffe\MVCNNDataLayer.py, 3708 , 2019-01-04
mvcnn-master\caffe\MVCNNDataLayerPreTrain.py, 3211 , 2019-01-04
mvcnn-master\caffe\README.md, 600 , 2019-01-04
mvcnn-master\caffe\alexNet.prototxt, 5384 , 2019-01-04
mvcnn-master\caffe\ilsvrc_2012_mean.npy, 1572944 , 2019-01-04
mvcnn-master\caffe\mvccn_12view.prototxt, 6102 , 2019-01-04
mvcnn-master\caffe\mvcnn_PreTrain.prototxt, 249 , 2019-01-04
mvcnn-master\caffe\mvcnn_Train.prototxt, 263 , 2019-01-04
mvcnn-master\caffe\trainAlex.py, 321 , 2019-01-04
mvcnn-master\caffe\trainCNN.py, 333 , 2019-01-04
mvcnn-master\caffe\trainMVCNN.py, 318 , 2019-01-04
mvcnn-master\cnn_shape.m, 7128 , 2019-01-04
mvcnn-master\cnn_shape_get_batch.m, 4605 , 2019-01-04
mvcnn-master\cnn_shape_get_features.m, 12834 , 2019-01-04
mvcnn-master\cnn_shape_init.m, 6412 , 2019-01-04
mvcnn-master\cnn_shape_train.m, 16907 , 2019-01-04
mvcnn-master\contributors.txt, 56 , 2019-01-04
mvcnn-master\data, 0 , 2019-01-04
mvcnn-master\data\.gitignore, 25 , 2019-01-04
mvcnn-master\dataset, 0 , 2019-01-04
mvcnn-master\dataset\setup_imdb_generic.m, 102 , 2019-01-04
mvcnn-master\dataset\setup_imdb_modelnet.m, 8592 , 2019-01-04
mvcnn-master\dataset\setup_imdb_shapenet.m, 3249 , 2019-01-04
mvcnn-master\dependencies, 0 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96, 0 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\.gitignore, 31 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\COPYRIGHT, 1486 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\Makefile, 993 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\Makefile.win, 900 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\README, 20224 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\blas, 0 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\blas\Makefile, 293 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\blas\blas.h, 702 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\blas\blasp.h, 16529 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\blas\daxpy.c, 1274 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\blas\ddot.c, 1280 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\blas\dnrm2.c, 1375 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\blas\dscal.c, 1104 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\heart_scale, 27670 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\linear.cpp, 57430 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\linear.def, 426 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\linear.h, 2211 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\matlab, 0 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\matlab\Makefile, 1504 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\matlab\README, 7470 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\matlab\libsvmread.c, 4063 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\matlab\libsvmwrite.c, 2341 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\matlab\linear_model_matlab.c, 3545 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\matlab\linear_model_matlab.h, 166 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\matlab\make.m, 1139 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\matlab\predict.c, 8517 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\matlab\train.c, 10861 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\predict.c, 5338 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\python, 0 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\python\Makefile, 32 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\python\README, 12195 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\python\liblinear.py, 9373 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\python\liblinearutil.py, 8208 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\train.c, 9109 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\tron.cpp, 5186 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\tron.h, 687 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\windows, 0 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\windows\liblinear.dll, 182272 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\windows\libsvmread.mexw64, 11264 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\windows\libsvmwrite.mexw64, 10240 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\windows\predict.exe, 128512 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\windows\predict.mexw64, 16896 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\windows\train.exe, 179200 , 2019-01-04
mvcnn-master\dependencies\liblinear-1.96\windows\train.mexw64, 61440 , 2019-01-04
mvcnn-master\dependencies\matconvnet, 0 , 2019-01-04
mvcnn-master\dependencies\vlfeat, 0 , 2019-01-04
mvcnn-master\evalkit, 0 , 2019-01-04
mvcnn-master\evalkit\Evaluator.js, 5553 , 2019-01-04
mvcnn-master\evalkit\Metrics.js, 4769 , 2019-01-04
mvcnn-master\evalkit\README.txt, 1148 , 2019-01-04
mvcnn-master\evalkit\evaluate.js, 150 , 2019-01-04
mvcnn-master\evalkit\train.csv, 894149 , 2019-01-04
mvcnn-master\evalkit\val.csv, 128999 , 2019-01-04
mvcnn-master\exp_scripts, 0 , 2019-01-04
mvcnn-master\exp_scripts\confmat.m, 321 , 2019-01-04
mvcnn-master\exp_scripts\display_retrieval_results.m, 3539 , 2019-01-04
mvcnn-master\exp_scripts\display_right_wrong.m, 3109 , 2019-01-04
mvcnn-master\exp_scripts\learn_metric.m, 1634 , 2019-01-04
mvcnn-master\exp_scripts\prfigure.m, 1756 , 2019-01-04
mvcnn-master\exp_scripts\visualize_saliency.m, 2931 , 2019-01-04
mvcnn-master\get_imdb.m, 840 , 2019-01-04
mvcnn-master\rerank_retrieval.m, 1330 , 2019-01-04
mvcnn-master\run_experiments.m, 2384 , 2019-01-04
mvcnn-master\run_retrieval.m, 2471 , 2019-01-04
mvcnn-master\setup.m, 2522 , 2019-01-04
mvcnn-master\shape_compute_descriptor.m, 5257 , 2019-01-04
mvcnn-master\utils, 0 , 2019-01-04
mvcnn-master\utils\RenderMe, 0 , 2019-01-04
mvcnn-master\utils\RenderMe\RenderDepth, 0 , 2019-01-04

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • CUDA C编程权威指南_源码
    (全 全 全)CUDA C编程权威指南_源码(Programming Authoritative Guide_Source Code)
    2021-01-05 12:38:54下载
    积分:1
  • PokemonGo-Bot-master
    PokemonGo-Bot-master 寶可夢Bot功能(PokemonGo Bot function)
    2020-06-23 12:40:01下载
    积分:1
  • 速度距离欺骗干扰 matlab Method IV
    说明:  速度距离欺骗干扰,用于雷达欺骗式干扰,用于matlab仿真(Velocity Distance Deception Jammings,for radar deception jamming and MATLAB simulation.)
    2021-01-05 19:08:54下载
    积分:1
  • TestForWeChat
    说明:  可以捕捉微信窗口,并且可以实现定时的消息发送(It can capture wechat window and send messages regularly)
    2021-01-01 20:59:03下载
    积分:1
  • devcl55s
    说明:  dvexpress 安装工具,个人收藏,拿出来分享,希望能帮到需要的人(DELPHIER biginner i hope which is your favor and can help you to do resolve some trouble things)
    2020-06-17 20:20:07下载
    积分:1
  • 八数码问题的源代码
    八数码问题的源代码-eight digital source of the problem
    2022-08-22 23:24:58下载
    积分:1
  • 快捷鍵
    在IntelliJ IDEA 2018.3.2 x64里面使用eclipse快捷键的全部快捷代码(the is IntelliJ IDEA 2018.3.2 x64eclipse thenk)
    2019-05-24 14:39:58下载
    积分:1
  • This is the windows API programming vc procedures, can help quickly familiar wit...
    这个是有关windows API编程的vc程序,可帮助迅速熟悉windows API-This is the windows API programming vc procedures, can help quickly familiar with the windows API
    2023-05-20 07:40:03下载
    积分:1
  • chap1
    希望广大学习通信原理的来看一下,这就是我们学校的通信原理课件,希望能对大家有用(We hope that the study look at communication theory, this is our school' s communication theory courseware, hoping it would be useful)
    2010-08-05 12:01:37下载
    积分:1
  • JAVA 扫雷小游戏,JFRAM框架下,16×16 ,默认40个雷,可以设置雷的数量...
    JAVA 扫雷小游戏,JFRAM框架下,16×16 ,默认40个雷,可以设置雷的数量-Mine JAVA games, JFRAM framework, 16 × 16, the default 40 mine, you can set the number of mines
    2022-06-12 16:46:57下载
    积分:1
  • 696518资源总数
  • 104269会员总数
  • 31今日下载