zeal-up
zeal-up
I notice that you make a real-world demo that demonstrates estimating the pose of real ycb-v objects. I cannot find where to buy these this object. Can you give some...
Thanks for your jobs! It's nice to release the pretrained models. I think it will be useful if you release some performances of the released models.
Since when download cctexture always abort sometimes with internet issue, sometimes the request target is not a zip file and the script raises an exception. I add two features: 1....
When approximate the initial filters kernel gθ(Λ) = diag(θ) with a polynomial  why we can‘t simply combine the eigenvector and eigenvalue matrix together like  because  * The...
Thanks for your jobs! This repo is well organized and help me a lot. I want to know how many GPUs did you use when training a Resnet101 on UCF101...
Thanks for sharing your work. I am interesting in whether can this pointsift module used in a classification task? Have you done some experiment about classification?
Hi, thanks for your job. I have some question about the svm training and testing precedure. According to your paper, you randomly rotate the pointcloud and extract the features. Dose...
My environment: cuda10.0 pytroch1.2/1.4 python3.6 I have successfully compiled index_max and the module is installed in 'xx/xx/python3.6/site-packages/index_max-0.0.0-py3.6-linux-x86_64.egg/index_max.cpython-36m-x86_64-linux-gnu.so'. However, when I try to import index_max, it raised up an error: ```...
Have anyone train a VGG19 network used this code? I used the total exactly the same code in the repository except using a lr_schuduler to change the learning rate automatically....
1. 按照身高从低到高排序,身高相同,k大的排在前面 2. 从后往前搜索,将每一个people往后移动k次 这样做能达到目的的原因是:当我们先将身高从低到高排序,任意元素往后移动,并不会影响后面元素的合理性。 并且,不需要额外空间存储,也就不需要是用链表。空间复杂度是O(1) ``` class Solution { static bool peopleCompare(vector& pre, vector& next) { if (pre[0] != next[0]) return pre[0] < next[0]; else { return pre[1] >...