Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Ansheng You"'
Autor:
Yunhai Tong, Xia Li, Zhouchen Lin, Xiangtai Li, Guangliang Cheng, Ansheng You, Li Zhang, Kuiyuan Yang
Publikováno v:
IEEE Transactions on Image Processing. 30:7050-7063
Graph-based convolutional model such as non-local block has shown to be effective for strengthening the context modeling ability in convolutional neural networks (CNNs). However, its pixel-wise computational overhead is prohibitive which renders it u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::59cddd570a9e550ae4615dd2bdf6e778
https://doi.org/10.1109/tip.2021.3099369
https://doi.org/10.1109/tip.2021.3099369
Publikováno v:
AAAI
With the advance of omnidirectional panoramic technology, 360◦ imagery has become increasingly popular in the past few years. To better understand the 360◦ content, many works resort to the 360◦ object detection and various criteria have been p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c22ae4a33282e5df6ff8ab3445f7d35a
https://doi.org/10.1609/aaai.v34i07.6995
https://doi.org/10.1609/aaai.v34i07.6995
Autor:
Xiangzeng Zhou, Yingya Zhang, Wang Bin, Yu Liu, Ming Li, Pan Pan, Lianghua Huang, Ansheng You, Xu Yinghui
Publikováno v:
ACM Multimedia
Videos grow to be one of the largest mediums on the Internet. E-commerce platforms like Alibaba need to process millions of video data across multimedia (e.g., visual, audio, image, and text) and on a variety of tasks (e.g., retrieval, tagging, and s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c90cadbd6bfbf9e5318d5763efb6417a
https://doi.org/10.1145/3474085.3481541
https://doi.org/10.1145/3474085.3481541
Publikováno v:
KDD
In contrast to regular convolutions with local receptive fields, non-local operations have widely proven an effective method for modeling long-range dependencies. Although lots of prior works have been proposed, prohibitive computation and GPU memory
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f8e83ae417f3aae26ce5f56eb5308822
https://doi.org/10.1145/3447548.3467239
https://doi.org/10.1145/3447548.3467239
Publikováno v:
ACM Multimedia
Adaptive and flexible image editing is a desirable function of modern generative models. In this work, we present a generative model with auto-encoder architecture for per-region style manipulation. We apply a code consistency loss to enforce an expl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56653d5fdb6e7e30e0c07da0f7903497
Publikováno v:
CVPR
In this paper, we focus on semantically multi-modal image synthesis (SMIS) task, namely, generating multi-modal images at the semantic level. Previous work seeks to use multiple class-specific generators, constraining its usage in datasets with a sma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ea7e8ae19e94133d2ec5f37f723d3ef
https://doi.org/10.1109/cvpr42600.2020.00551
https://doi.org/10.1109/cvpr42600.2020.00551
Autor:
Shaohua Tan, Ansheng You, Yunhai Tong, Kuiyuan Yang, Maoke Yang, Zhen Zhu, Houlong Zhao, Xiangtai Li
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030584511
ECCV (1)
ECCV (1)
In this paper, we focus on designing effective method for fast and accurate scene parsing. A common practice to improve the performance is to attain high resolution feature maps with strong semantic representation. Two strategies are widely used—at
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b567822879a86ab0e2208b0cfe8b935c
https://doi.org/10.1007/978-3-030-58452-8_45
https://doi.org/10.1007/978-3-030-58452-8_45