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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

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