Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Arun Sacheti"'
Autor:
Nan Duan, Lei Ji, Edward Cui, Ming Zhong, Huaishao Luo, Taroon Bharti, Lin Su, Chenfei Wu, Arun Sacheti, Yongfei Liu
Publikováno v:
ACL/IJCNLP (Findings)
In this paper, we present GEM as a General Evaluation benchmark for Multimodal tasks. Different from existing datasets such as GLUE, SuperGLUE, XGLUE and XTREME that mainly focus on natural language tasks, GEM is a large-scale vision-language benchma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ebb754706939654e6ffd6e4ad6b538e8
Autor:
Xi Chen, Meenaz Merchant, Huang Jiapei, Houdong Hu, Yan Wang, Wu Ye, Arun Sacheti, Linjun Yang, Pavel Komlev, Huang Li
Publikováno v:
KDD
In this paper, we introduce a web-scale general visual search system deployed in Microsoft Bing. The system accommodates tens of billions of images in the index, with thousands of features for each image, and can respond in less than 200 ms. In order
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f79dbc0cbb15e66b92a7cb35fccf1cb3
Autor:
Liang, Wanying1 (AUTHOR) sylvialaung@m.scnu.edu.cn, Meo, Pasquale De2 (AUTHOR) pasquale.demeo@unime.it, Tang, Yong1,3 (AUTHOR) ytang@m.scnu.edu.cn, Zhu, Jia4 (AUTHOR) jiazhu@zjnu.edu.cn
Publikováno v:
ACM Computing Surveys. Nov2024, Vol. 56 Issue 11, p1-41. 41p.
Autor:
Zhao, Fei1 (AUTHOR) larry5@uab.edu, Zhang, Chengcui1 (AUTHOR) czhang02@uab.edu, Geng, Baocheng1 (AUTHOR) bgeng@uab.edu
Publikováno v:
ACM Computing Surveys. Sep2024, Vol. 56 Issue 9, p1-36. 36p.
Publikováno v:
ACM Transactions on Multimedia Computing, Communications & Applications; Mar2024, Vol. 20 Issue 3, p1-23, 23p
Autor:
MESSINA, NICOLA, AMATO, GIUSEPPE, ESULI, ANDREA, FALCHI, FABRIZIO, GENNARO, CLAUDIO, MARCHAND-MAILLET, STÉPHANE
Publikováno v:
ACM Transactions on Multimedia Computing, Communications & Applications; Nov2021, Vol. 17 Issue 4, p1-23, 23p
Publikováno v:
Proceedings of the Fourth ACM International Conference: Web Search & Data Mining; 2/ 9/2011, p395-404, 10p
Autor:
Barz, Björn
Content-based Image Retrieval (CBIR) ist ein Verfahren zum Auffinden von Bildern in großen Datenbanken wie z. B. dem Internet anhand ihres Inhalts. Ausgehend von einem vom Nutzer bereitgestellten Anfragebild, gibt das System eine sortierte Liste äh
The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefu