2D Image-Based 3D Scene Retrieval
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Date
2018
Authors
Abdul-Rashid, Hameed
Yuan, Juefei
Li, Bo
Lu, Yijuan
Bai, Song
Bai, Xiang
Bui, Ngoc-Minh
Do, Minh N.
Do, Trong-Le
Duong, Anh-Duc
He, Xinwei
Le, Tu-Khiem
Li, Wenhui
Liu, Anan
Liu, Xiaolong
Nguyen, Khac-Tuan
Nguyen, Vinh-Tiep
Nie, Weizhi
Ninh, Van-Tu
Su, Yuting
Ton-That, Vinh
Tran, Minh-Triet
Xiang, Shu
Zhou, Heyu
Zhou, Yang
Zhou, Zhichao
Yuan, Juefei
Li, Bo
Lu, Yijuan
Bai, Song
Bai, Xiang
Bui, Ngoc-Minh
Do, Minh N.
Do, Trong-Le
Duong, Anh-Duc
He, Xinwei
Le, Tu-Khiem
Li, Wenhui
Liu, Anan
Liu, Xiaolong
Nguyen, Khac-Tuan
Nguyen, Vinh-Tiep
Nie, Weizhi
Ninh, Van-Tu
Su, Yuting
Ton-That, Vinh
Tran, Minh-Triet
Xiang, Shu
Zhou, Heyu
Zhou, Yang
Zhou, Zhichao
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
2D scene image-based 3D scene retrieval is a new research topic in the field of 3D object retrieval. Given a 2D scene image, it is to search for relevant 3D scenes from a dataset. It has an intuitive and convenient framework which allows users to learn, search, and utilize the retrieved results for vast related applications, such as automatic 3D content generation for 3D movie, game and animation production, robotic vision, and consumer electronics apps development, and autonomous vehicles. To advance this promising research, we organize this SHREC track and build the first 2D scene image-based 3D scene retrieval benchmark by collecting 2D images from ImageNet and 3D scenes from Google 3D Warehouse. The benchmark contains uniformly classified 10,000 2D scene images and 1,000 3D scene models of ten (10) categories. In this track, seven (7) groups from five countries (China, Chile, USA, UK, and Vietnam) have registered for the track, while due to many challenges involved, only three (3) groups have successfully submitted ten (10) runs of five methods. To have a comprehensive comparison, seven (7) commonly-used retrieval performance metrics have been used to evaluate their retrieval performance. We also suggest several future research directions for this research topic. We wish this publicly available [ARYLL18] benchmark, comparative evaluation results and corresponding evaluation code, will further enrich and boost the research of 2D scene image-based 3D scene retrieval and its applications.
Description
@inproceedings{10.2312:3dor.20181051,
booktitle = {Eurographics Workshop on 3D Object Retrieval},
editor = {Telea, Alex and Theoharis, Theoharis and Veltkamp, Remco},
title = {{2D Image-Based 3D Scene Retrieval}},
author = {Abdul-Rashid, Hameed and Yuan, Juefei and He, Xinwei and Le, Tu-Khiem and Li, Wenhui and Liu, Anan and Liu, Xiaolong and Nguyen, Khac-Tuan and Nguyen, Vinh-Tiep and Nie, Weizhi and Ninh, Van-Tu and Su, Yuting and Li, Bo and Ton-That, Vinh and Tran, Minh-Triet and Xiang, Shu and Zhou, Heyu and Zhou, Yang and Zhou, Zhichao and Lu, Yijuan and Bai, Song and Bai, Xiang and Bui, Ngoc-Minh and Do, Minh N. and Do, Trong-Le and Duong, Anh-Duc},
year = {2018},
publisher = {The Eurographics Association},
ISSN = {1997-0471},
ISBN = {978-3-03868-053-6},
DOI = {10.2312/3dor.20181051}
}