Zobrazeno 1 - 10
of 971
pro vyhledávání: '"Zhang Ziming"'
Autor:
Zhang, Ziming, Shao, Yuping, Zhang, Yiqing, Lin, Fangzhou, Zhang, Haichong, Rundensteiner, Elke
Iterative methods such as iterative closest point (ICP) for point cloud registration often suffer from bad local optimality (e.g. saddle points), due to the nature of nonconvex optimization. To address this fundamental challenge, in this paper we pro
Externí odkaz:
http://arxiv.org/abs/2411.10649
3D point cloud classification requires distinct models from 2D image classification due to the divergent characteristics of the respective input data. While 3D point clouds are unstructured and sparse, 2D images are structured and dense. Bridging the
Externí odkaz:
http://arxiv.org/abs/2410.09691
Publikováno v:
ICWSM 2024
Wildlife trafficking (WLT) has emerged as a global issue, with traffickers expanding their operations from offline to online platforms, utilizing e-commerce websites and social networks to enhance their illicit trade. This paper addresses the challen
Externí odkaz:
http://arxiv.org/abs/2409.16671
Autor:
Lin, Fangzhou, Liu, Haotian, Zhou, Haoying, Hou, Songlin, Yamada, Kazunori D, Fischer, Gregory S., Li, Yanhua, Zhang, Haichong K., Zhang, Ziming
3D point clouds enhanced the robot's ability to perceive the geometrical information of the environments, making it possible for many downstream tasks such as grasp pose detection and scene understanding. The performance of these tasks, though, heavi
Externí odkaz:
http://arxiv.org/abs/2409.06171
Autor:
Ma, Xihan, Zeng, Mingjie, Hill, Jeffrey C., Hoffmann, Beatrice, Zhang, Ziming, Zhang, Haichong K.
Navigating the ultrasound (US) probe to the standardized imaging plane (SIP) for image acquisition is a critical but operator-dependent task in conventional freehand diagnostic US. Robotic US systems (RUSS) offer the potential to enhance imaging cons
Externí odkaz:
http://arxiv.org/abs/2406.11523
In recent years, there has been a growing trend of incorporating hyperbolic geometry methods into computer vision. While these methods have achieved state-of-the-art performance on various metric learning tasks using hyperbolic distance measurements,
Externí odkaz:
http://arxiv.org/abs/2404.15523
Publikováno v:
International Journal of Applied Mathematics and Computer Science, Vol 34, Iss 3, Pp 453-466 (2024)
Visual question answering (VQA) is a pivotal topic at the intersection of computer vision and natural language processing. This paper addresses the challenges of linguistic bias and bias fusion within invalid regions encountered in existing VQA model
Externí odkaz:
https://doaj.org/article/eec635c84bd4463895fd10d7e217acc3
The Lucas-Kanade (LK) method is a classic iterative homography estimation algorithm for image alignment, but often suffers from poor local optimality especially when image pairs have large distortions. To address this challenge, in this paper we prop
Externí odkaz:
http://arxiv.org/abs/2303.11526
To learn distinguishable patterns, most of recent works in vehicle re-identification (ReID) struggled to redevelop official benchmarks to provide various supervisions, which requires prohibitive human labors. In this paper, we seek to achieve the sim
Externí odkaz:
http://arxiv.org/abs/2303.11169
Learning good image representations that are beneficial to downstream tasks is a challenging task in computer vision. As such, a wide variety of self-supervised learning approaches have been proposed. Among them, contrastive learning has shown compet
Externí odkaz:
http://arxiv.org/abs/2302.01409