Giter VIP home page Giter VIP logo

tvnet's Introduction

End-to-End Learning of Motion Representation for Video Understanding

This repository contains implementation code for the project 'End-to-End Learning of Motion Representation for Video Understanding' (CVPR 2018).

http://lijiefan.me/project_webpage/TVNet_cvpr/index.html

Prerequisites

Tensorflow

We use tensorflow (https://www.tensorflow.org) for our implementation.

Matlab (optional)

We use .mat file for TVNet generated results saving, and Matlab for results visualization.

Installation

Our current release has been tested on Ubuntu 16.04.

Clone the repository

git clone https://github.com/LijieFan/tvnet.git

Steps to run

I) Put input frames in frame/img1.png, frame/img2.png.

II) Use TVNet to generate motion representation

The file (demo.py) has the following options:

  • -scale: Number of scales in TVNet (default: 1)
  • -warp: Number of warppings in TVNet (default: 1)
  • -iteration: Number of iterations in TVNet(default: 50)
  • -gpu: the gpu to run on (0-indexed, -1 for CPU)

Sample usages include

  • Generate motion representation for frames in frame/img1.png and frame/img2.png.
python demo.py --scale 1 --warp 1 --iteration 50 --gpu 1

III) Check results and visualization

-TVNet generated results are saved in result/result.mat

-Use the MPI-Sintel tool box for result visualization. In matlab, run run visualize/visualize.m.

Sample input & output

Acknowledgement

We’d love to express out appreciation to Jian Guo for the useful discussions during the course of this research.

Reference

if you find our code useful for your research, please cite our paper:

@inproceedings{fan2018end,
title={End-to-End Learning of Motion Representation for Video Understanding},
author={Fan, Lijie and Huang, Wenbing and Gan, Chuang and Ermon, Stefano and Gong, Boqing and Huang, Junzhou},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
pages={},
year={2018}
}

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.