Category: Uncategorized

  • Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

    Today we released the paper, together with code and modes, of our AAAI 2018 publication “Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition“. This work is one of my most liked papers in recent years. It provides an elegant way to deal with temporal dynamic graphs such as skeleton sequences. Without any feature or…

  • Kinetics Pretrained TSN Models Released

    Kinetics Human Action Video Dataset is a large-scale video action recognition dataset released by Google DeepMind. It contains around 300,000 trimmed human action videos from 400 action classes. This year (2017), it served in the ActivityNet challenge as the trimmed video classification track. During our participation in the challenge, we have confirmed that our TSN framework published in ECCV 2016 works smoothly on…

  • Squeezing Memory out of Caffe

    No, I am not talking about thinking of the good old days with a cup of drink. Today we are talking about our recent release of a new feature in our modified version of deep learning toolbox, Caffe. https://github.com/yjxiong/caffe In this release, we have implemented the functionality usually referred to as “memory multiloading”. A Wiki…

  • ECCV Paper: Temporal Segment Networks: Towards Good Practices in Deep Action Recognition

    We just released the code for Temporal Segment Networks (TSN) accepted to ECCV 2016. Github: Temporal Segment Networks In this release, we not only want to showcase the research work, but also mean to provide an accessible framework that will lower the barrier of entrance for research in action recognition or more general video understanding.…

  • Caffe Install Guide Ubuntu 15.10

    For those who are seeking help for installing Caffe on Ubuntu 15.10, here comes the cure. Linked is a detailed guided tour from our good friend, Ruohui Wang. Compile and run Caffe on Ubuntu 15.10

  • Intel 终于也注意到deep learning的问题了

    Single Node Caffe Scoring and Training on Intel® Xeon E5-Series Processors With these optimizations time to train AlexNet* network on full ILSVRC-2012 dataset to 80% top5 accuracy reduces from 58 days to about 5 days. LOL.

  • Supercharge Caffe with MPI Parallelism

    Our fork of Caffe at Github Repo Features MPI-based data/hybrid parallelism, low communication overhead Almost transparent parallel support Scaling up to multiple GPU and machines, with Ethernet/Infiniband Video data input.

  • Monte da Rocha Dam,今天的Bing桌面

    Pretty.   搜索Monte da Rocha Dam,更多美景

  • Thrust Tips

    Thrust 是一个基于CUDA实现STL模板库。 今天在用的时候发现一个问题,后来解决了,记录一下以备将来使用。 问题就是:Thrust暂时不支持Debug信息生成。所以在调用Thrust的文件不能开启NVCC的-G开关。具体操作方式如下(以VS2010为例): 1.在Solution Explorer里面右击对应的.cu文件,然后进入properties->Configuration Properties-> Device->Generate GPU Debug Information,选择No. 否则可能出现各种Thrust::System_error  

  • 新年第一篇

    2014年就这样到来了,新的一年总是充满着希望与可能。 在这一年,愿每一个人都能离自己的梦想更近,离苦难更远。 愿每一天,都有更真实的体验。