Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Benjamin Caine"'
Autor:
Zhaoqi Leng, Shuyang Cheng, Benjamin Caine, Weiyue Wang, Xiao Zhang, Jonathon Shlens, Mingxing Tan, Dragomir Anguelov
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031198205
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c3b2021161ab1defa4d8205c2a7dbc05
https://doi.org/10.1007/978-3-031-19821-2_32
https://doi.org/10.1007/978-3-031-19821-2_32
Autor:
Benjamin Caine, Xiao Zhang, Vijay K. Vasudevan, Pei Sun, Yuning Chai, Dragomir Anguelov, Jiquan Ngiam, Weiyue Wang
Publikováno v:
CVPR
3D object detection is vital for many robotics applications. For tasks where a 2D perspective range image exists, we propose to learn a 3D representation directly from this range image view. To this end, we designed a 2D convolutional network archite
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f0db6f85a4bc31549d05197ecdd5a585
Autor:
Wei Han, Yuning Chai, Yin Zhou, Vijaysai Patnaik, Pei Sun, Henrik Kretzschmar, Aurelien Chouard, Xerxes Dotiwalla, Aditya Joshi, Maxim Krivokon, Benjamin Caine, Amy Gao, Paul Tsui, Vijay K. Vasudevan, Dragomir Anguelov, Zhifeng Chen, Aleksei Timofeev, Yu Zhang, Hang Zhao, Scott Ettinger, Jonathon Shlens, James Guo, Jiquan Ngiam
Publikováno v:
CVPR
The research community has increasing interest in autonomous driving research, despite the resource intensity of obtaining representative real world data. Existing self-driving datasets are limited in the scale and variation of the environments they
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dd0cf2d0666dae2a235855318fd92edb
https://doi.org/10.1109/cvpr42600.2020.00252
https://doi.org/10.1109/cvpr42600.2020.00252
Autor:
Zhengdong Zhang, Ouais Alsharif, Benjamin Caine, Brandon Yang, Zhifeng Chen, Jonathon Shlens, Christoph Sprunk, Vijay K. Vasudevan, Jiquan Ngiam, Wei Han
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585228
ECCV (18)
ECCV (18)
Autonomous vehicles operate in a dynamic environment, where the speed with which a vehicle can perceive and react impacts the safety and efficacy of the system. LiDAR provides a prominent sensory modality that informs many existing perceptual systems
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa3422eb4646307fb17b24a46cdd6126
https://doi.org/10.1007/978-3-030-58523-5_25
https://doi.org/10.1007/978-3-030-58523-5_25
Autor:
Ekin D. Cubuk, Zhaoqi Leng, Chunyan Bai, Jonathon Shlens, Jiquan Ngiam, Vijay K. Vasudevan, Dragomir Anguelov, Shuyang Cheng, Barret Zoph, Benjamin Caine, Congcong Li, Quoc V. Le, Yang Song
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585884
ECCV (21)
ECCV (21)
Data augmentation has been widely adopted for object detection in 3D point clouds. However, all previous related efforts have focused on manually designing specific data augmentation methods for individual architectures. In this work, we present the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6459d7bd81253675ef7311ee28bbdf0c
https://doi.org/10.1007/978-3-030-58589-1_17
https://doi.org/10.1007/978-3-030-58589-1_17