Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Rongfei Jia"'
Publikováno v:
International Journal of Computer Vision. 129:3313-3337
The 3D CAD shapes in current 3D benchmarks are mostly collected from online model repositories. Thus, they typically have insufficient geometric details and less informative textures, making them less attractive for comprehensive and subtle research
Publikováno v:
Proceedings of the VLDB Endowment. 14:320-328
With the rapid growth of e-commerce in recent years, e-commerce platforms are becoming a primary place for people to find, compare and ultimately purchase products. To improve online shopping experience for consumers and increase sales for sellers, i
In this work, we tackle the problem of single image-based 3D shape retrieval (IBSR), where we seek to find the most matched shape of a given single 2D image from a shape repository. Most of the existing works learn to embed 2D images and 3D shapes in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bbbea297aaa47f6c69c720fd0d917b6b
https://orca.cardiff.ac.uk/id/eprint/143849/1/ImageShapeRetrieval_ICCV2021.pdf
https://orca.cardiff.ac.uk/id/eprint/143849/1/ImageShapeRetrieval_ICCV2021.pdf
Autor:
Jian Zhang, Yuanqing Zhang, Huan Fu, Xiaowei Zhou, Bowen Cai, Jinchi Huang, Rongfei Jia, Binqiang Zhao, Xing Tang
Neural Radiance Fields (NeRF) have emerged as a potent paradigm for representing scenes and synthesizing photo-realistic images. A main limitation of conventional NeRFs is that they often fail to produce high-quality renderings under novel viewpoints
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::122ce604d45ad24ed5649bd70644cb72
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200700
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::03a1de0a79082d5a2112f404ba245ca3
https://doi.org/10.1007/978-3-031-20071-7_18
https://doi.org/10.1007/978-3-031-20071-7_18
Autor:
Jian Zhang, Jinchi Huang, Bowen Cai, Huan Fu, Mingming Gong, Chaohui Wang, Jiaming Wang, Hongchen Luo, Rongfei Jia, Binqiang Zhao, Xing Tang
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031197833
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a847bc34d8e10c160454739276a7ff58
https://doi.org/10.1007/978-3-031-19784-0_42
https://doi.org/10.1007/978-3-031-19784-0_42
Autor:
Huan Fu, Bowen Cai, Lin Gao, Ling-Xiao Zhang, Jiaming Wang, Cao Li, Qixun Zeng, Chengyue Sun, Rongfei Jia, Binqiang Zhao, Hao Zhang
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision (ICCV).
Autor:
Chengfei Lv, Tie Luo, Lifeng Hua, Fan Wu, Hongtao Lv, Shaojie Tang, Zhenzhe Zheng, Rongfei Jia
Publikováno v:
WiOpt
Federated learning (FL) trains a machine learning model on mobile devices in a distributed manner using each device's private data and computing resources. A critical issues is to evaluate individual users' contributions so that (1) users' effort in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2923b52d99b09254ad59b2579961acbe
http://arxiv.org/abs/2108.10623
http://arxiv.org/abs/2108.10623
Autor:
Rongfei Jia, Shaojie Tang, Fan Wu, Chaoyue Niu, Guihai Chen, Lifeng Hua, Chengfei Lv, Zhihua Wu
Publikováno v:
MobiCom
Federated learning was proposed with an intriguing vision of achieving collaborative machine learning among numerous clients without uploading their private data to a cloud server. However, the conventional framework requires each client to leverage
Autor:
Rongfei Jia, Ling Jiang, Yuhong Zhou, Yan Wang, Xi Guo, Yuan Ji, Xiang Ni, Xiaoyan Yang, Jia, Rongfei, Jiang, Ling, Zhou, Yuhong, Wang, Yan, Guo, Xi, Ji, Yuan, Ni, Xiang, Yang, Xiaoyan
Publikováno v:
Medicine; 8/21/2020, Vol. 99 Issue 34, p1-6, 6p