Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Zheng-Ning Liu"'
Publikováno v:
Computational Visual Media, Vol 9, Iss 4, Pp 733-752 (2023)
Abstract While originally designed for natural language processing tasks, the self-attention mechanism has recently taken various computer vision areas by storm. However, the 2D nature of images brings three challenges for applying self-attention in
Externí odkaz:
https://doaj.org/article/cdd0ef47e2e94c739261b252d46dde56
Publikováno v:
Computational Visual Media, Vol 9, Iss 2, Pp 401-404 (2023)
Abstract
Externí odkaz:
https://doaj.org/article/ee0de94524a2484da0e75171019cf9cd
Publikováno v:
Computational Visual Media, Vol 7, Iss 3, Pp 283-288 (2021)
Externí odkaz:
https://doaj.org/article/afbaa95097f945ff847cf3fbdf8a4b51
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics. :1-14
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9441b8ee6b5c2003bfea2f231a758ad
https://doi.org/10.1109/tvcg.2023.3257035
https://doi.org/10.1109/tvcg.2023.3257035
Publikováno v:
Computational Visual Media, Vol 7, Iss 3, Pp 283-288 (2021)
In the first week of May, 2021, researchers from four different institutions: Google, Tsinghua University, Oxford University and Facebook, shared their latest work [16, 7, 12, 17] on arXiv.org almost at the same time, each proposing new learning arch
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::42ee883016bc4c77f79852a76ed7b49c
https://doi.org/10.1007/s41095-021-0240-x
https://doi.org/10.1007/s41095-021-0240-x
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3dff220be40b2a11123992e7e9a26f79
https://doi.org/10.2139/ssrn.4313526
https://doi.org/10.2139/ssrn.4313526
Attention mechanisms, especially self-attention, have played an increasingly important role in deep feature representation for visual tasks. Self-attention updates the feature at each position by computing a weighted sum of features using pair-wise a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::795739b84b198061d3f4e7dec11c2c1e
http://arxiv.org/abs/2105.02358
http://arxiv.org/abs/2105.02358
Autor:
Meng-Hao Guo, Tian-Xing Xu, Jiang-Jiang Liu, Zheng-Ning Liu, Peng-Tao Jiang, Tai-Jiang Mu, Song-Hai Zhang, Ralph R. Martin, Ming-Ming Cheng, Shi-Min Hu
Humans can naturally and effectively find salient regions in complex scenes. Motivated by this observation, attention mechanisms were introduced into computer vision with the aim of imitating this aspect of the human visual system. Such an attention
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b762df9c505a2fd4850c3edd9414e3e4
Autor:
Shi-Min Hu, Zheng-Ning Liu, Meng-Hao Guo, Jun-Xiong Cai, Jiahui Huang, Tai-Jiang Mu, Ralph R. Martin
Convolutional neural networks (CNNs) have made great breakthroughs in 2D computer vision. However, their irregular structure makes it hard to harness the potential of CNNs directly on meshes. A subdivision surface provides a hierarchical multi-resolu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc0f9efdbce6bf3caa3a3e579fda92be