Zobrazeno 1 - 10
of 111
pro vyhledávání: '"Xiao, Jianxiong"'
Publikováno v:
In Applied Mathematics and Computation 1 October 2022 430
Autor:
Seff, Ari, Xiao, Jianxiong
Today's autonomous vehicles rely extensively on high-definition 3D maps to navigate the environment. While this approach works well when these maps are completely up-to-date, safe autonomous vehicles must be able to corroborate the map's information
Externí odkaz:
http://arxiv.org/abs/1611.08583
Autor:
Zeng, Andy, Yu, Kuan-Ting, Song, Shuran, Suo, Daniel, Walker Jr., Ed, Rodriguez, Alberto, Xiao, Jianxiong
Robot warehouse automation has attracted significant interest in recent years, perhaps most visibly in the Amazon Picking Challenge (APC). A fully autonomous warehouse pick-and-place system requires robust vision that reliably recognizes and locates
Externí odkaz:
http://arxiv.org/abs/1609.09475
Autor:
Zeng, Andy, Song, Shuran, Nießner, Matthias, Fisher, Matthew, Xiao, Jianxiong, Funkhouser, Thomas
Matching local geometric features on real-world depth images is a challenging task due to the noisy, low-resolution, and incomplete nature of 3D scan data. These difficulties limit the performance of current state-of-art methods, which are typically
Externí odkaz:
http://arxiv.org/abs/1603.08182
While deep neural networks have led to human-level performance on computer vision tasks, they have yet to demonstrate similar gains for holistic scene understanding. In particular, 3D context has been shown to be an extremely important cue for scene
Externí odkaz:
http://arxiv.org/abs/1603.04922
Autor:
Xiao, Jianxiong
Thesis (Ph. D.)--Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 213-227).
On your one-minute walk
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 213-227).
On your one-minute walk
Externí odkaz:
http://hdl.handle.net/1721.1/84901
Autor:
Chang, Angel X., Funkhouser, Thomas, Guibas, Leonidas, Hanrahan, Pat, Huang, Qixing, Li, Zimo, Savarese, Silvio, Savva, Manolis, Song, Shuran, Su, Hao, Xiao, Jianxiong, Yi, Li, Yu, Fisher
We present ShapeNet: a richly-annotated, large-scale repository of shapes represented by 3D CAD models of objects. ShapeNet contains 3D models from a multitude of semantic categories and organizes them under the WordNet taxonomy. It is a collection o
Externí odkaz:
http://arxiv.org/abs/1512.03012
This paper describes a method for accelerating large scale Artificial Neural Networks (ANN) training using multi-GPUs by reducing the forward and backward passes to matrix multiplication. We propose an out-of-core multi-GPU matrix multiplication and
Externí odkaz:
http://arxiv.org/abs/1511.04348
Autor:
Song, Shuran, Xiao, Jianxiong
We focus on the task of amodal 3D object detection in RGB-D images, which aims to produce a 3D bounding box of an object in metric form at its full extent. We introduce Deep Sliding Shapes, a 3D ConvNet formulation that takes a 3D volumetric scene fr
Externí odkaz:
http://arxiv.org/abs/1511.02300
Basic Linear Algebra Subprograms (BLAS) are a set of low level linear algebra kernels widely adopted by applications involved with the deep learning and scientific computing. The massive and economic computing power brought forth by the emerging GPU
Externí odkaz:
http://arxiv.org/abs/1510.05041