Skip to content

Actionness Estimation Using Hybrid Fully Convolutional Networks

Notifications You must be signed in to change notification settings

xiaoanshi/Actionness-Estimation

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

10 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Actionness Estimation Using Hybrid FCNs

Here we provide the code of actionness estimation with hybrid fully convolutional networks from the following paper:

Actionness Estimation Using Hybrid Fully Convolutional Netoworks
Limin Wang, Yu Qiao, Xiaou Tang, and Luc Van Gool, in CVPR, 2016

Updates

  • Jul 22, 2016
    • Initilaize repo of actionness estimation.

Demo code

  • demo_a_fcn.m: an example showing actionness estimation with A-FCN.
  • demo_m_fcn.m: an example showing actionness estimation with M-FCN.
  • For optical flow extraction, we use TVL1 Optical Flow
    You need download our dense flow code and compile it by yourself. Dense Flow

Download

Questions

Contact

About

Actionness Estimation Using Hybrid Fully Convolutional Networks

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • MATLAB 100.0%