Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Nishiwaki, Koichi"'
Planar-symmetric hands, such as parallel grippers, are widely adopted in both research and industrial fields. Their symmetry, however, introduces ambiguity and discontinuity in the SO(3) representation, which hinders both the training and inference o
Externí odkaz:
http://arxiv.org/abs/2410.04826
In this paper, we propose a method to segment and recover a static, clean background and multiple 360$^\circ$ objects from observations of scenes at different timestamps. Recent works have used neural radiance fields to model 3D scenes and improved t
Externí odkaz:
http://arxiv.org/abs/2404.09426
Autor:
Ikeda, Takuya, Zakharov, Sergey, Ko, Tianyi, Irshad, Muhammad Zubair, Lee, Robert, Liu, Katherine, Ambrus, Rares, Nishiwaki, Koichi
This paper addresses the challenging problem of category-level pose estimation. Current state-of-the-art methods for this task face challenges when dealing with symmetric objects and when attempting to generalize to new environments solely through sy
Externí odkaz:
http://arxiv.org/abs/2402.12647
Learning-based grasp detectors typically assume a precision grasp, where each finger only has one contact point, and estimate the grasp probability. In this work, we propose a data generation and learning pipeline that can leverage power grasping, wh
Externí odkaz:
http://arxiv.org/abs/2312.11804
Category-level pose estimation is a challenging task with many potential applications in computer vision and robotics. Recently, deep-learning-based approaches have made great progress, but are typically hindered by the need for large datasets of eit
Externí odkaz:
http://arxiv.org/abs/2311.13777
In recent years, a deep learning framework has been widely used for object pose estimation. While quaternion is a common choice for rotation representation, it cannot represent the ambiguity of the observation. In order to handle the ambiguity, the B
Externí odkaz:
http://arxiv.org/abs/2305.18947
Autor:
Ko, Tianyi, Nishiwaki, Koichi, Terada, Koji, Tanaka, Yusuke, Mitsumata, Shun, Katagiri, Ryuichi, Junko, Taketo, Horiba, Naoshi, Igata, Hideyoshi, Mizuno, Kazue
In this paper, we present a robotic device for mouse tail vein injection. We propose a mouse holding mechanism to realize vein injection without anesthetizing the mouse, which consists of a tourniquet, vacuum port, and adaptive tail-end fixture. The
Externí odkaz:
http://arxiv.org/abs/2205.12756
In recent years, a deep learning framework has been widely used for object pose estimation. While quaternion is a common choice for rotation representation of 6D pose, it cannot represent an uncertainty of the observation. In order to handle the unce
Externí odkaz:
http://arxiv.org/abs/2203.04456
Autor:
Ikeda, Takuya, Tanishige, Suomi, Amma, Ayako, Sudano, Michael, Audren, Hervé, Nishiwaki, Koichi
In recent years, synthetic data has been widely used in the training of 6D pose estimation networks, in part because it automatically provides perfect annotation at low cost. However, there are still non-trivial domain gaps, such as differences in te
Externí odkaz:
http://arxiv.org/abs/2203.02069
Publikováno v:
Philosophical Transactions: Mathematical, Physical and Engineering Sciences, 2007 Jan . 365(1850), 79-107.
Externí odkaz:
https://www.jstor.org/stable/25190429
