Paper Info
Title
Actionet: An Interactive End-To-End Platform For Task-Based Data Collection And Augmentation In 3d Environment
Abstract
The problem of task planning for artificial agents remains largely unsolved. While there has been increasing interest in data-driven approaches for the study of task planning for artificial agents, a significant remaining bottleneck is the dearth of large-scale comprehensive task-based datasets. In this paper, we present ActioNet, an interactive end-to-end platform for data collection and augmentation of task-based dataset in 3D environment. Using ActioNet, we collected a large-scale comprehensive task-based dataset, comprising over 3000 hierarchical task structures and videos. Using the hierarchical task structures, the videos are further augmented across 50 different scenes to give over 150,000 video. To our knowledge, ActioNet is the first interactive end-to-end platform for such task-based dataset generation and the ac-companying dataset is the largest task-based dataset of such comprehensive nature. The ActioNet platform and dataset will be made available to facilitate research in hierarchical task planning.(1)
Year
DOI
Venue
2020
10.1109/ICIP40778.2020.9191324
2020 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
Keywords
DocType
ISSN
hierarchical task planning, artificial agent, platform, dataset, 3D environment
Conference
1522-4880
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Jiafei Duan100.34
Samson Yu211.04
Hui Li Tan3767.42
Cheston Tan415515.27