Skip to content

Tree-Structured Policy based Progressive Reinforcement Learning for Temporally Language Grounding in Video (AAAI2020)

Notifications You must be signed in to change notification settings

WuJie1010/TSP-PRL

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

31 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Tree-Structured Policy based Progressive Reinforcement Learning for Temporally Language Grounding in Video (AAAI2020)

This repository contains the pytorch codes and trained models described in the paper "Tree-Structured Policy based Progressive Reinforcement Learning for Temporally Language Grounding in Video" By Jie Wu, Guanbin Li, Si Liu, Liang Lin. Paper

Motivation

Motivation

Framework

Framework

Requirements

  • Python 2.7
  • Pytorch 0.4.1
  • matplotlib
  • The code is for Charades-STA dataset.

Visual Features

Please download the features in Features1, and put it in the "Dataset/Charades" folder.

Training and Testing Data

Please download the TrainingData in TrainingData, and put it in the "Dataset/Charades/ref_info" folder. Please download the TestingData in TestingData, and put it in the "Dataset/Charades/ref_info" folder.

Pre-trained models

We provide the pre-trained model for Charades-STA dataset, which can get 24.73 on R@1, IoU0.7 and 45.30 on R@1, IoU0.5: Models

Train

python train.py

Validate

python val.py

Test from Pre-trained Model

python test.py

About

Tree-Structured Policy based Progressive Reinforcement Learning for Temporally Language Grounding in Video (AAAI2020)

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages