GAIA-Universe: Everything is Super-Netify

doi:10.1109/TPAMI.2023.3276392

	GAIA-Universe: Everything is Super-Netify
	Peng, Junran1,2,3 ; Chang, Qing 1,2; Yin, Haoran 1,2; Bu, Xingyuan 4; Sun, Jiajun1,2 ; Xie, Lingxi 3; Zhang, Xiaopeng3 ; Tian, Qi 3; Zhang, Zhaoxiang1,2,5
发表期刊	IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
ISSN	0162-8828
	2023-10-01
卷号	45 期号:10 页码:11856-11868
通讯作者	Zhang, Zhaoxiang(zhaoxiang.zhang@ia.ac.cn)
摘要	Pre-training on large-scale datasets has played an increasingly significant role in computer vision and natural language processing recently. However, as there exist numerous application scenarios that have distinctive demands such as certain latency constraints and specialized data distributions, it is prohibitively expensive to take advantage of large-scale pre-training for per-task requirements. we focus on two fundamental perception tasks (object detection and semantic segmentation) and present a complete and flexible system named GAIA-Universe(GAIA), which could automatically and efficiently give birth to customized solutions according to heterogeneous downstream needs through data union and super-net training. GAIA is capable of providing powerful pre-trained weights and searching models that conform to downstream demands such as hardware constraints, computation constraints, specified data domains, and telling relevant data for practitioners who have very few datapoints on their tasks. With GAIA, we achieve promising results on COCO, Objects365, Open Images, BDD100 k, and UODB which is a collection of datasets including KITTI, VOC, WiderFace, DOTA, Clipart, Comic, and more. Taking COCO as an example, GAIA is able to efficiently produce models covering a wide range of latency from 16 ms to 53 ms, and yields AP from 38.2 to 46.5 without whistles and bells. GAIA is released at https://github.com/GAIA-vision.
关键词	Computer vision object detection semantic segmentation AutoML
DOI	10.1109/TPAMI.2023.3276392
收录类别	SCI
语种	英语
资助项目	Major Project for New Generation of AI ; National Natural Science Foundation of China[2018AAA0100400] ; National Natural Science Foundation of China[61836014] ; National Natural Science Foundation of China[U21B2042] ; National Natural Science Foundation of China[62072457] ; InnoHK program ; [62006231]
项目资助者	Major Project for New Generation of AI ; National Natural Science Foundation of China ; InnoHK program
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:001068816800023
出版者	IEEE COMPUTER SOC
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/53036
专题	多模态人工智能系统全国重点实验室
通讯作者	Zhang, Zhaoxiang
作者单位	1.Chinese Acad Sci CASIA, Ctr Res Intelligent Percept & Comp CRIPAC, Inst Automat, Natl Lab Pattern Recognit NLPR, Beijing 100045, Peoples R China 2.Univ Chinese Acad Sci UCAS, Beijing 100190, Peoples R China 3.Huawei Technol Inc, Beijing 100190, Peoples R China 4.Beijing Inst Technol, Beijing 100190, Peoples R China 5.Ctr Excellence Brain Sci & Intelligence Technol CE, Ctr Artificial Intelligence & Robot, HKISICAS, Beijing 100190, Peoples R China
第一作者单位	模式识别国家重点实验室
通讯作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Peng, Junran,Chang, Qing,Yin, Haoran,et al. GAIA-Universe: Everything is Super-Netify[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2023,45(10):11856-11868.
APA	Peng, Junran.,Chang, Qing.,Yin, Haoran.,Bu, Xingyuan.,Sun, Jiajun.,...&Zhang, Zhaoxiang.(2023).GAIA-Universe: Everything is Super-Netify.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,45(10),11856-11868.
MLA	Peng, Junran,et al."GAIA-Universe: Everything is Super-Netify".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 45.10(2023):11856-11868.