Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Lin, Jianxin"'
Autor:
Yin, Lianying, Wang, Yijun, He, Tianyu, Liu, Jinming, Zhao, Wei, Li, Bohan, Jin, Xin, Lin, Jianxin
Although previous co-speech gesture generation methods are able to synthesize motions in line with speech content, it is still not enough to handle diverse and complicated motion distribution. The key challenges are: 1) the one-to-many nature between
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3391be7b06854c492f989cf3a029cf34
As a recent noticeable topic, domain generalization aims to learn a generalizable model on multiple source domains, which is expected to perform well on unseen test domains. Great efforts have been made to learn domain-invariant features by aligning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7f8585c113daca216e6f36c66d39bd1
Publikováno v:
Fuel. 326:125094
Publikováno v:
Dianzi Jishu Yingyong, Vol 45, Iss 1, Pp 19-22 (2019)
Aiming at overcoming the drawback that a conventional power divider can only operate at a fixed frequency and its odd harmonics, a miniaturized unequal power divider operating at 1 GHz and 2.2 GHz is presented. The miniaturization is achieved by real
Autor:
Lin, Jianxin
Superconducting quantum interference devices (SQUIDs) are used in an impressively large variety of applications requiring sensitive detection of magnetic flux. In recent years, there has been a growing scientific and technological interest in the dev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______707::ae98d71b9747d8bcf41daabf46f17227
https://hdl.handle.net/10900/106120
https://hdl.handle.net/10900/106120
Hybrid-distorted image restoration (HD-IR) is dedicated to restore real distorted image that is degraded by multiple distortions. Existing HD-IR approaches usually ignore the inherent interference among hybrid distortions which compromises the restor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::01f602365cb156184e94b9b4ff99353d
http://arxiv.org/abs/2007.11430
http://arxiv.org/abs/2007.11430
An unsupervised image-to-image translation (UI2I) task deals with learning a mapping between two domains without paired images. While existing UI2I methods usually require numerous unpaired images from different domains for training, there are many s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c7f2a11a8e34a65376cbe6a9d125691e
http://arxiv.org/abs/2004.04634
http://arxiv.org/abs/2004.04634
Most existing image restoration networks are designed in a disposable way and catastrophically forget previously learned distortions when trained on a new distortion removal task. To alleviate this problem, we raise the novel lifelong image restorati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b82afc165155e4bf716fecda47409502
Unsupervised domain translation has recently achieved impressive performance with Generative Adversarial Network (GAN) and sufficient (unpaired) training data. However, existing domain translation frameworks form in a disposable way where the learnin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd330cea42386648224ffc7296decfea
http://arxiv.org/abs/1906.00181
http://arxiv.org/abs/1906.00181