Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Zhou, Shunbo"'
Autor:
Han, Chenrui, Yu, Xuan, Xie, Yuxuan, Liu, Yili, Mao, Sitong, Zhou, Shunbo, Xiong, Rong, Wang, Yue
Interactive point cloud segmentation has become a pivotal task for understanding 3D scenes, enabling users to guide segmentation models with simple interactions such as clicks, therefore significantly reducing the effort required to tailor models to
Externí odkaz:
http://arxiv.org/abs/2407.14009
Autor:
Yu, Xuan, Liu, Yili, Han, Chenrui, Mao, Sitong, Zhou, Shunbo, Xiong, Rong, Liao, Yiyi, Wang, Yue
Panoptic reconstruction is a challenging task in 3D scene understanding. However, most existing methods heavily rely on pre-trained semantic segmentation models and known 3D object bounding boxes for 3D panoptic segmentation, which is not available f
Externí odkaz:
http://arxiv.org/abs/2407.01349
The performance of image super-resolution relies heavily on the accuracy of degradation information, especially under blind settings. Due to absence of true degradation models in real-world scenarios, previous methods learn distinct representations b
Externí odkaz:
http://arxiv.org/abs/2407.01299
Although visual navigation has been extensively studied using deep reinforcement learning, online learning for real-world robots remains a challenging task. Recent work directly learned from offline dataset to achieve broader generalization in the re
Externí odkaz:
http://arxiv.org/abs/2404.10675
LiDAR Mapping has been a long-standing problem in robotics. Recent progress in neural implicit representation has brought new opportunities to robotic mapping. In this paper, we propose the multi-volume neural feature fields, called NF-Atlas, which b
Externí odkaz:
http://arxiv.org/abs/2304.04624
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Existing works on control of tractor-trailers systems only consider the kinematics model without taking dynamics into account. Also, most of them treat the issue as a pure control theory problem whose solutions are difficult to implement. This paper
Externí odkaz:
http://arxiv.org/abs/1909.11897
Autor:
Liu, Zhe, Suo, Chuanzhe, Zhou, Shunbo, Wei, Huanshu, Liu, Yingtian, Wang, Hesheng, Liu, Yun-Hui
Place recognition and loop-closure detection are main challenges in the localization, mapping and navigation tasks of self-driving vehicles. In this paper, we solve the loop-closure detection problem by incorporating the deep-learning based point clo
Externí odkaz:
http://arxiv.org/abs/1904.13030
In this paper, we focus on the problem of task allocation, cooperative path planning and motion coordination of the large-scale system with thousands of robots, aiming for practical applications in robotic warehouses and automated logistics systems.
Externí odkaz:
http://arxiv.org/abs/1904.01303
Point cloud based place recognition is still an open issue due to the difficulty in extracting local features from the raw 3D point cloud and generating the global descriptor, and it's even harder in the large-scale dynamic environments. In this pape
Externí odkaz:
http://arxiv.org/abs/1812.07050