Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Xia Zhaoyang"'
Autor:
Wu, Junda, Zhang, Zhehao, Xia, Yu, Li, Xintong, Xia, Zhaoyang, Chang, Aaron, Yu, Tong, Kim, Sungchul, Rossi, Ryan A., Zhang, Ruiyi, Mitra, Subrata, Metaxas, Dimitris N., Yao, Lina, Shang, Jingbo, McAuley, Julian
Multimodal large language models (MLLMs) equip pre-trained large-language models (LLMs) with visual capabilities. While textual prompting in LLMs has been widely studied, visual prompting has emerged for more fine-grained and free-form visual instruc
Externí odkaz:
http://arxiv.org/abs/2409.15310
Publikováno v:
Open Chemistry, Vol 16, Iss 1, Pp 99-107 (2018)
There are a number of secondary metabolites having medicinal values in Ligustri Lucidi Fructus. In this study, the target analytes salidroside, ligustroflavone, specnuezhenide, oleuropein, oleanolic acid and ursolic acid were chosen, aiming to establ
Externí odkaz:
https://doaj.org/article/c44d6deb64af4a2b80e2091c4749b58f
Autor:
Liu, Youquan, Chen, Runnan, Li, Xin, Kong, Lingdong, Yang, Yuchen, Xia, Zhaoyang, Bai, Yeqi, Zhu, Xinge, Ma, Yuexin, Li, Yikang, Qiao, Yu, Hou, Yuenan
Point-, voxel-, and range-views are three representative forms of point clouds. All of them have accurate 3D measurements but lack color and texture information. RGB images are a natural complement to these point cloud views and fully utilizing the c
Externí odkaz:
http://arxiv.org/abs/2309.05573
Autor:
Liu, Yang, Xia, Zhaoyang, Zhao, Mengyang, Wei, Donglai, Wang, Yuzheng, Siao, Liu, Ju, Bobo, Fang, Gaoyun, Liu, Jing, Song, Liang
Video anomaly detection is an essential yet challenging task in the multimedia community, with promising applications in smart cities and secure communities. Existing methods attempt to learn abstract representations of regular events with statistica
Externí odkaz:
http://arxiv.org/abs/2308.01537
Autor:
Han, Ligong, Wen, Song, Chen, Qi, Zhang, Zhixing, Song, Kunpeng, Ren, Mengwei, Gao, Ruijiang, Stathopoulos, Anastasis, He, Xiaoxiao, Chen, Yuxiao, Liu, Di, Zhangli, Qilong, Jiang, Jindong, Xia, Zhaoyang, Srivastava, Akash, Metaxas, Dimitris
DDIM inversion has revealed the remarkable potential of real image editing within diffusion-based methods. However, the accuracy of DDIM reconstruction degrades as larger classifier-free guidance (CFG) scales being used for enhanced editing. Null-tex
Externí odkaz:
http://arxiv.org/abs/2306.05414
Autor:
Cheng, Kai, Zeng, Xinhua, Liu, Yang, Wang, Tian, Pang, Chengxin, Teng, Jing, Xia, Zhaoyang, Liu, Jing
Video anomaly detection (VAD) is a vital task with great practical applications in industrial surveillance, security system, and traffic control. Unlike previous unsupervised VAD methods that adopt a fixed structure to learn normality without conside
Externí odkaz:
http://arxiv.org/abs/2305.07328
Autor:
Xia, Zhaoyang, Liu, Youquan, Li, Xin, Zhu, Xinge, Ma, Yuexin, Li, Yikang, Hou, Yuenan, Qiao, Yu
Training deep models for semantic scene completion (SSC) is challenging due to the sparse and incomplete input, a large quantity of objects of diverse scales as well as the inherent label noise for moving objects. To address the above-mentioned probl
Externí odkaz:
http://arxiv.org/abs/2303.06884
The generalization for different scenarios and dif-ferent users is an urgent problem for millimeter wave gesture recognition for indoor fiber-to-the-room (FTTR) scenario. In order to solve this problem and verify the feasibility of FTTR Q-band millim
Externí odkaz:
http://arxiv.org/abs/2208.00837
Autor:
Chen, Yuxiao, Zhao, Long, Yuan, Jianbo, Tian, Yu, Xia, Zhaoyang, Geng, Shijie, Han, Ligong, Metaxas, Dimitris N.
Despite the success of fully-supervised human skeleton sequence modeling, utilizing self-supervised pre-training for skeleton sequence representation learning has been an active field because acquiring task-specific skeleton annotations at large scal
Externí odkaz:
http://arxiv.org/abs/2207.09644
Autor:
Liu, Di, Gao, Yunhe, Zhangli, Qilong, Han, Ligong, He, Xiaoxiao, Xia, Zhaoyang, Wen, Song, Chang, Qi, Yan, Zhennan, Zhou, Mu, Metaxas, Dimitris
Combining information from multi-view images is crucial to improve the performance and robustness of automated methods for disease diagnosis. However, due to the non-alignment characteristics of multi-view images, building correlation and data fusion
Externí odkaz:
http://arxiv.org/abs/2203.10726