Zobrazeno 1 - 10
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pro vyhledávání: '"Chen, ZhiQiang"'
Simultaneous Localization and Mapping (SLAM) is pivotal in robotics, with photorealistic scene reconstruction emerging as a key challenge. To address this, we introduce Computational Alignment for Real-Time Gaussian Splatting SLAM (CaRtGS), a novel m
Externí odkaz:
http://arxiv.org/abs/2410.00486
The human brain exhibits a strong ability to spontaneously associate different visual attributes of the same or similar visual scene, such as associating sketches and graffiti with real-world visual objects, usually without supervising information. I
Externí odkaz:
http://arxiv.org/abs/2409.18694
Autor:
Chen, Zhiqiang, Qi, Yuhua, Feng, Dapeng, Zhuang, Xuebin, Chen, Hongbo, Hu, Xiangcheng, Wu, Jin, Peng, Kelin, Lu, Peng
The ability to estimate pose and generate maps using 3D LiDAR significantly enhances robotic system autonomy. However, existing open-source datasets lack representation of geometrically degenerate environments, limiting the development and benchmarki
Externí odkaz:
http://arxiv.org/abs/2409.04961
Autor:
Wang, Yuang, Yoon, Siyeop, Jin, Pengfei, Tivnan, Matthew, Song, Sifan, Chen, Zhennong, Hu, Rui, Zhang, Li, Li, Quanzheng, Chen, Zhiqiang, Wu, Dufan
Diffusion-based models are widely recognized for their effectiveness in image restoration tasks; however, their iterative denoising process, which begins from Gaussian noise, often results in slow inference speeds. The Image-to-Image Schr\"odinger Br
Externí odkaz:
http://arxiv.org/abs/2403.06069
Autor:
Chen, Zhiqiang, Chen, Hongbo, Qi, Yuhua, Zhong, Shipeng, Feng, Dapeng, Jin, Wu, Wen, Weisong, Liu, Ming
Publikováno v:
published in ICRA 2024
LiDAR-based localization is valuable for applications like mining surveys and underground facility maintenance. However, existing methods can struggle when dealing with uninformative geometric structures in challenging scenarios. This paper presents
Externí odkaz:
http://arxiv.org/abs/2402.18934
Autor:
Zhong, Shipeng, Chen, Hongbo, Qi, Yuhua, Feng, Dapeng, Chen, Zhiqiang, Wu, Jin, Wen, Weisong, Liu, Ming
Publikováno v:
published in ICRA 2024
Collaborative state estimation using different heterogeneous sensors is a fundamental prerequisite for robotic swarms operating in GPS-denied environments, posing a significant research challenge. In this paper, we introduce a centralized system to f
Externí odkaz:
http://arxiv.org/abs/2402.11790
Publikováno v:
Journal of Knowledge Management, 2024, Vol. 28, Issue 8, pp. 2197-2219.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JKM-12-2022-0965
Autor:
Han, Yifeng, Chen, Cui-Qun, Sun, Hualei, Zhao, Shuang, Jiang, Long, Liu, Yuxuan, Sun, Zhongxiong, Wang, Meng, Dong, Hongliang, Zhang, Ziyou, Chen, Zhiqiang, Chen, Bin, Yao, Dao-Xin, Li, Man-Rong
Publikováno v:
Materials Today Physics 40,101309 (2024)
Transition-metal honeycomb compounds are capturing scientific attention due to their distinctive electronic configurations, underscored by the triangular-lattice spin-orbit coupling and competition between multiple interactions, paving the way for po
Externí odkaz:
http://arxiv.org/abs/2310.20341
Autor:
Huang, Chaoxin, Huo, Mengwu, Huang, Xing, Liu, Hui, Li, Lisi, Zhang, Ziyou, Chen, Zhiqiang, Han, Yifeng, Chen, Lan, Liang, Feixiang, Dong, Hongliang, Shen, Bing, Sun, Hualei, Wang, Meng
Ferrimagnetic nodal-line semiconductor Mn$_3$Si$_2$Te$_6$ keeps the records of colossal magnetoresistance (CMR) and angular magnetoresistance (AMR). Here we report tuning the electronic transport properties via doping and pressure in (Mn$_{1-x}$Mg$_x
Externí odkaz:
http://arxiv.org/abs/2309.05945
Autor:
GUAN Liang, ZHANG Ji, YUE Caijun, CHEN Zhiqiang, CHEN Xi, CHEN Minhao, YAN Jihong, ZENG Zhihua
Publikováno v:
Qixiang keji, Vol 52, Iss 5, Pp 704-713 (2024)
There are many ships and ports in Shanghai coastal zones, where disastrous weather occurs frequently. Meteorological disasters often threaten the safety of people’s lives and properties along the coast and in the ports. In the past, the meteorologi
Externí odkaz:
https://doaj.org/article/b04fa0833f0d4cf786f5c5252f9709ef