L
Li-Jia Li
Researcher at Google
Publications - 63
Citations - 19825
Li-Jia Li is an academic researcher from Google. The author has contributed to research in topics: Object (computer science) & Object detection. The author has an hindex of 39, co-authored 63 publications receiving 15096 citations. Previous affiliations of Li-Jia Li include University of Illinois at Urbana–Champaign & Carnegie Mellon University.
Papers
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Journal ArticleDOI
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
Ranjay Krishna,Yuke Zhu,Oliver Groth,Justin Johnson,Kenji Hata,Joshua Kravitz,Stephanie Chen,Yannis Kalantidis,Li-Jia Li,David A. Shamma,Michael S. Bernstein,Li Fei-Fei +11 more
TL;DR: The Visual Genome dataset as mentioned in this paper contains over 108k images where each image has an average of $35$35 objects, $26$26 attributes, and $21$21 pairwise relationships between objects.
Posted Content
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
Ranjay Krishna,Yuke Zhu,Oliver Groth,Justin Johnson,Kenji Hata,Joshua Kravitz,Stephanie Chen,Yannis Kalantidis,Li-Jia Li,David A. Shamma,Michael S. Bernstein,Fei-Fei Li +11 more
TL;DR: The Visual Genome dataset is presented, which contains over 108K images where each image has an average of $$35$$35 objects, $$26$$26 attributes, and $$21$$21 pairwise relationships between objects, and represents the densest and largest dataset of image descriptions, objects, attributes, relationships, and question answer pairs.
Book ChapterDOI
Progressive Neural Architecture Search
Chenxi Liu,Barret Zoph,Maxim Neumann,Jonathon Shlens,Wei Hua,Li-Jia Li,Li Fei-Fei,Li Fei-Fei,Alan L. Yuille,Jonathan Huang,Kevin Murphy +10 more
TL;DR: In this article, a sequential model-based optimization (SMBO) strategy is proposed to search for structures in order of increasing complexity, while simultaneously learning a surrogate model to guide the search through structure space.
Journal ArticleDOI
YFCC100M: the new data in multimedia research
Bart Thomee,David A. Shamma,Gerald Friedland,Benjamin Elizalde,Karl Ni,Douglas N. Poland,Damian Borth,Li-Jia Li +7 more
TL;DR: This publicly available curated dataset of almost 100 million photos and videos is free and legal for all.
Book ChapterDOI
AMC: AutoML for Model Compression and Acceleration on Mobile Devices
TL;DR: This paper proposes AutoML for Model Compression (AMC) which leverages reinforcement learning to efficiently sample the design space and can improve the model compression quality and achieves state-of-the-art model compression results in a fully automated way without any human efforts.