Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Zheng, Jingxiao"'
Autor:
Zheng, Jingxiao, Shi, Xinwei, Gorban, Alexander, Mao, Junhua, Song, Yang, Qi, Charles R., Liu, Ting, Chari, Visesh, Cornman, Andre, Zhou, Yin, Li, Congcong, Anguelov, Dragomir
3D human pose estimation (HPE) in autonomous vehicles (AV) differs from other use cases in many factors, including the 3D resolution and range of data, absence of dense depth maps, failure modes for LiDAR, relative location between the camera and LiD
Externí odkaz:
http://arxiv.org/abs/2112.12141
Unconstrained video-based face recognition is a challenging problem due to significant within-video variations caused by pose, occlusion and blur. To tackle this problem, an effective idea is to propagate the identity from high-quality faces to low-q
Externí odkaz:
http://arxiv.org/abs/1905.02756
Autor:
Zheng, Jingxiao, Ranjan, Rajeev, Chen, Ching-Hui, Chen, Jun-Cheng, Castillo, Carlos D., Chellappa, Rama
Although deep learning approaches have achieved performance surpassing humans for still image-based face recognition, unconstrained video-based face recognition is still a challenging task due to large volume of data to be processed and intra/inter-v
Externí odkaz:
http://arxiv.org/abs/1812.04058
Autor:
Ranjan, Rajeev, Bansal, Ankan, Zheng, Jingxiao, Xu, Hongyu, Gleason, Joshua, Lu, Boyu, Nanduri, Anirudh, Chen, Jun-Cheng, Castillo, Carlos D., Chellappa, Rama
The availability of large annotated datasets and affordable computation power have led to impressive improvements in the performance of CNNs on various object detection and recognition benchmarks. These, along with a better understanding of deep lear
Externí odkaz:
http://arxiv.org/abs/1809.07586
We address the recognition of agent-in-place actions, which are associated with agents who perform them and places where they occur, in the context of outdoor home surveillance. We introduce a representation of the geometry and topology of scene layo
Externí odkaz:
http://arxiv.org/abs/1804.01429
Autor:
Bodla, Navaneeth, Zheng, Jingxiao, Xu, Hongyu, Chen, Jun-Cheng, Castillo, Carlos, Chellappa, Rama
Although deep learning has yielded impressive performance for face recognition, many studies have shown that different networks learn different feature maps: while some networks are more receptive to pose and illumination others appear to capture mor
Externí odkaz:
http://arxiv.org/abs/1702.04471
Autor:
Gong, Yuchuan, Guo, Hongtao, Liu, Xiyuan, Zheng, Jingxiao, Zhang, Teng, Que, Luying, Jia, Conghan, Ou, Guangbin, Jiao, Xiben, Liu, Zherong, Chang, Liang, Zhou, Liang, Zhou, Jun
Publikováno v:
Circuits and Systems II: Express Briefs, IEEE Transactions on; 2024, Vol. 71 Issue: 5 p2794-2798, 5p
Publikováno v:
Functional Materials Letters; Aug2023, Vol. 16 Issue 6, p1-4, 4p
Autor:
Zheng, Jingxiao, Shi, Xinwei, Gorban, Alexander, Mao, Junhua, Song, Yang, Qi, Charles R., Liu, Ting, Chari, Visesh, Cornman, Andre, Zhou, Yin, Li, Congcong, Anguelov, Dragomir
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
3D human pose estimation (HPE) in autonomous vehicles (AV) differs from other use cases in many factors, including the 3D resolution and range of data, absence of dense depth maps, failure modes for LiDAR, relative location between the camera and LiD
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1695e13929cec5dba397a3e26963afe
https://doi.org/10.1109/cvprw56347.2022.00494
https://doi.org/10.1109/cvprw56347.2022.00494
Autor:
Zheng, Jingxiao
Face recognition is one of the active areas of research in computer vision and biometrics. Many approaches have been proposed in the literature that demonstrate impressive performance, especially those based on deep learning. However, unconstrained f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::159b5d644785a34c5357b009fd564fff