Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Wang, Brian H."'
Path planning in obstacle-dense environments is a key challenge in robotics, and depends on inferring scene attributes and associated uncertainties. We present a multiple-hypothesis path planner designed to navigate complex environments using obstacl
Externí odkaz:
http://arxiv.org/abs/2308.07420
We present a method for detecting and mapping trees in noisy stereo camera point clouds, using a learned 3-D object detector. Inspired by recent advancements in 3-D object detection using a pseudo-lidar representation for stereo data, we train a Poin
Externí odkaz:
http://arxiv.org/abs/2103.15967
Autor:
Wang, Brian H., Chao, Wei-Lun, Wang, Yan, Hariharan, Bharath, Weinberger, Kilian Q., Campbell, Mark
Object segmentation in three-dimensional (3-D) point clouds is a critical task for robots capable of 3-D perception. Despite the impressive performance of deep learning-based approaches on object segmentation in 2-D images, deep learning has not been
Externí odkaz:
http://arxiv.org/abs/1910.13955
Autor:
Wang, Yan, Lai, Zihang, Huang, Gao, Wang, Brian H., van der Maaten, Laurens, Campbell, Mark, Weinberger, Kilian Q.
Many applications of stereo depth estimation in robotics require the generation of accurate disparity maps in real time under significant computational constraints. Current state-of-the-art algorithms force a choice between either generating accurate
Externí odkaz:
http://arxiv.org/abs/1810.11408
We present a data association method for vision-based multiple pedestrian tracking, using deep convolutional features to distinguish between different people based on their appearances. These re-identification (re-ID) features are learned such that t
Externí odkaz:
http://arxiv.org/abs/1810.08565
Publikováno v:
In IFAC PapersOnLine 2019 51(34):176-183
Publikováno v:
Journal of Speech, Language & Hearing Research. Dec2003, Vol. 46 Issue 6, p1367-1377. 11p. 3 Charts, 1 Graph.