Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Dinh-Cuong Hoang"'
Autor:
Dinh-Cuong Hoang, Phan Xuan Tan, Duc-Long Pham, Hai-Nam Pham, Son-Anh Bui, Chi-Minh Nguyen, An-Binh Phi, Khanh-Duong Tran, Viet-Anh Trinh, van-Duc Tran, Duc-Thanh Tran, van-Hiep Duong, Khanh-Toan Phan, van-Thiep Nguyen, van-Duc Vu, Thu-Uyen Nguyen
Publikováno v:
IEEE Access, Vol 12, Pp 113810-113825 (2024)
Hand pose estimation is vital for various applications, including virtual reality (VR), augmented reality (AR), gesture recognition, human-computer interaction (HCI), and robotics. Achieving accurate and real-time hand pose estimation is challenging
Externí odkaz:
https://doaj.org/article/edf2a986abc242aaa142600934b92122
Autor:
Dinh-Cuong Hoang, Phan Xuan Tan, Thu-Uyen Nguyen, Hai-Nam Pham, Chi-Minh Nguyen, Son-Anh Bui, Quang-Tri Duong, van-Duc Vu, van-Thiep Nguyen, van-Hiep Duong, Ngoc-Anh Hoang, Khanh-Toan Phan, Duc-Thanh Tran, Ngoc-Trung Ho, Cong-Trinh Tran
Publikováno v:
IEEE Access, Vol 12, Pp 111723-111740 (2024)
Monocular Depth Estimation (MDE) and Object Pose Estimation (OPE) are important tasks in visual scene understanding. Traditionally, these challenges have been addressed independently, with separate deep neural networks designed for each task. However
Externí odkaz:
https://doaj.org/article/97e0579edc2f4935916bbf4c13471bb8
Autor:
Dinh-Cuong Hoang, Phan Xuan Tan, Anh-Nhat Nguyen, Duy-Quang Vu, van-Duc Vu, Thu-Uyen Nguyen, Quang-Tri Duong, van-Thiep Nguyen, Ngoc-Anh Hoang, Khanh-Toan Phan, Duc-Thanh Tran, Ngoc-Trung Ho, Cong-Trinh Tran, van-Hiep Duong, Phuc-Quan Ngo
Publikováno v:
IEEE Access, Vol 12, Pp 65444-65461 (2024)
The task of object pose estimation in computer vision heavily relies on both color (RGB) and depth (D) images to provide crucial appearance and geometric information, assisting algorithms in understanding occlusions and object geometry, thereby enhan
Externí odkaz:
https://doaj.org/article/eaf5dd85de7143fa80698f742364f8b4
Autor:
Phan Xuan Tan, Dinh-Cuong Hoang, Anh-Nhat Nguyen, Van-Thiep Nguyen, Van-Duc Vu, Thu-Uyen Nguyen, Ngoc-Anh Hoang, Khanh-Toan Phan, Duc-Thanh Tran, Duy-Quang Vu, Phuc-Quan Ngo, Quang-Tri Duong, Ngoc-Trung Ho, Cong-Trinh Tran, Van-Hiep Duong, Anh-Truong Mai
Publikováno v:
IEEE Access, Vol 12, Pp 65041-65057 (2024)
Grasp detection plays a pivotal role in robotic manipulation, allowing robots to interact with and manipulate objects in their surroundings. Traditionally, this has relied on three-dimensional (3D) point cloud data acquired from specialized depth cam
Externí odkaz:
https://doaj.org/article/2baca48e38a14321af705b871b34f43e
Autor:
Dinh-Cuong Hoang, Phan Xuan Tan, Anh-Nhat Nguyen, Duy-Quang Vu, Van-Duc Vu, Thu-Uyen Nguyen, Ngoc-Anh Hoang, Khanh-Toan Phan, Duc-Thanh Tran, Van-Thiep Nguyen, Quang-Tri Duong, Ngoc-Trung Ho, Cong-Trinh Tran, Van-Hiep Duong, Phuc-Quan Ngo
Publikováno v:
IEEE Access, Vol 12, Pp 54339-54351 (2024)
Hand-object configuration recovery is an important task in computer vision. The estimation of pose and shape for both hands and objects during interactive scenarios has various applications, particularly in augmented reality, virtual reality, or imit
Externí odkaz:
https://doaj.org/article/28cab9981f8549d09855c1e48f7f023d
Autor:
Van-Duc Vu, Dinh-Dai Hoang, Phan Xuan Tan, Van-Thiep Nguyen, Thu-Uyen Nguyen, Ngoc-Anh Hoang, Khanh-Toan Phan, Duc-Thanh Tran, Duy-Quang Vu, Phuc-Quan Ngo, Quang-Tri Duong, Anh-Nhat Nguyen, Dinh-Cuong Hoang
Publikováno v:
IEEE Access, Vol 12, Pp 1927-1942 (2024)
Accurate detection and estimation of pallet poses from color and depth data (RGB-D) are integral components many in advanced warehouse intelligent systems. State-of-the art object pose estimation methods follow a two-stage process, relying on off-the
Externí odkaz:
https://doaj.org/article/85818809aecf417c88c5ae9dd093fb5d
Autor:
Repetckiia O.V., Dinh Cuong Hoang
Publikováno v:
E3S Web of Conferences, Vol 363, p 01044 (2022)
Externí odkaz:
https://doaj.org/article/bf5703d2a6b345b7b90909c1cb865222
Publikováno v:
2022 International Conference on Robotics and Automation (ICRA)
IEEE Robotics and Automation Letters
IEEE Robotics and Automation Letters
Conventional methods to autonomous grasping rely on a pre-computed database with known objects to synthesize grasps, which is not possible for novel objects. On the other hand, recently proposed deep learning-based approaches have demonstrated the ab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8dc33a08cf2da91fd7b7bb256538f01
http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-98437
http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-98437
Autor:
Alessandro Palleschi, Marco Gugliotta, Chiara Gabellieri, Dinh-Cuong Hoang, Todor Stoyanov, Manolo Garabini, Lucia Pallottino
Despite the strong demand for solutions and the intense research effort, fully autonomous object manipulation is not yet solved. One of the main challenges is the large variety of conditions in which the objects should be handled. There is a need for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c2bc08181d9f88ec64a388238163f60
Publikováno v:
Applied Sciences, Vol 6, Iss 5, p 132 (2016)
The paper is concerned with the problem of multi-view three-dimensional (3D) point cloud registration. A novel global registration method is proposed to accurately register two series of scans into an object model underlying 3D imaging digitization b
Externí odkaz:
https://doaj.org/article/f54989a2e8b8412fb25e11e3692687ea