Zobrazeno 1 - 10
of 262
pro vyhledávání: '"LIU Weiquan"'
Autonomous vehicles (AVs) rely on LiDAR sensors for environmental perception and decision-making in driving scenarios. However, ensuring the safety and reliability of AVs in complex environments remains a pressing challenge. To address this issue, we
Externí odkaz:
http://arxiv.org/abs/2412.13017
RGB-D has gradually become a crucial data source for understanding complex scenes in assisted driving. However, existing studies have paid insufficient attention to the intrinsic spatial properties of depth maps. This oversight significantly impacts
Externí odkaz:
http://arxiv.org/abs/2409.07995
3D synthetic-to-real unsupervised domain adaptive segmentation is crucial to annotating new domains. Self-training is a competitive approach for this task, but its performance is limited by different sensor sampling patterns (i.e., variations in poin
Externí odkaz:
http://arxiv.org/abs/2403.18469
Autor:
Lin, Xiuhong, Qiu, Changjie, Cai, Zhipeng, Shen, Siqi, Zang, Yu, Liu, Weiquan, Bian, Xuesheng, Müller, Matthias, Wang, Cheng
Event cameras have emerged as a promising vision sensor in recent years due to their unparalleled temporal resolution and dynamic range. While registration of 2D RGB images to 3D point clouds is a long-standing problem in computer vision, no prior wo
Externí odkaz:
http://arxiv.org/abs/2311.18433
Autor:
Shen, Siqi, Ma, Chennan, Li, Chao, Liu, Weiquan, Fu, Yongquan, Mei, Songzhu, Liu, Xinwang, Wang, Cheng
Multi-agent systems are characterized by environmental uncertainty, varying policies of agents, and partial observability, which result in significant risks. In the context of Multi-Agent Reinforcement Learning (MARL), learning coordinated and decent
Externí odkaz:
http://arxiv.org/abs/2311.01753
Existing point cloud modeling datasets primarily express the modeling precision by pose or trajectory precision rather than the point cloud modeling effect itself. Under this demand, we first independently construct a set of LiDAR system with an opti
Externí odkaz:
http://arxiv.org/abs/2304.04200
Although 3D point cloud classification neural network models have been widely used, the in-depth interpretation of the activation of the neurons and layers is still a challenge. We propose a novel approach, named Relevance Flow, to interpret the hidd
Externí odkaz:
http://arxiv.org/abs/2303.06652
As the key technology of augmented reality (AR), 3D recognition and tracking are always vulnerable to adversarial examples, which will cause serious security risks to AR systems. Adversarial examples are beneficial to improve the robustness of the 3D
Externí odkaz:
http://arxiv.org/abs/2303.06641
Autor:
Bian, Xuesheng, Wang, Cheng, Chen, Shuting, Liu, Weiquan, Xu, Sen, Zhu, Jinxin, Wang, Rugang, Chen, Zexin, Huang, Min, Li, Gang
Adenosine triphosphate (ATP) is a high-energy phosphate compound and the most direct energy source in organisms. ATP is an essential biomarker for evaluating cell viability in biology. Researchers often use ATP bioluminescence to measure the ATP of o
Externí odkaz:
http://arxiv.org/abs/2303.06796
Autor:
Yang, Weikang, Lu, Xinghao, Chen, Binjie, Lin, Chenlu, Bao, Xueye, Liu, Weiquan, Zang, Yu, Xu, Junyu, Wang, Cheng
Publikováno v:
In International Journal of Applied Earth Observation and Geoinformation December 2024 135
