Paper Info
Title
ChainerCV: a Library for Deep Learning in Computer Vision.
Abstract
Despite significant progress of deep learning in the field of computer vision, there has not been a software library that covers these methods in a unifying manner. We introduce ChainerCV, a software library that is intended to fill this gap. ChainerCV supports numerous neural network models as well as software components needed to conduct research in computer vision. These implementations emphasize simplicity, flexibility and good software engineering practices. The library is designed to perform on par with the results reported in published papers and its tools can be used as a baseline for future research in computer vision. Our implementation includes sophisticated models like Faster R-CNN and SSD, and covers tasks such as object detection and semantic segmentation.
Year
DOI
Venue
2017
10.1145/3123266.3129395
MM '17: ACM Multimedia Conference Mountain View California USA October, 2017
Keywords
DocType
Volume
Open Source, Computer Vision, Machine Learning, Deep Learning
Journal
abs/1708.08169
ISBN
Citations 
PageRank 
978-1-4503-4906-2
7
0.47
References 
Authors
8
4
Name
Order
Citations
PageRank
Yusuke Niitani1151.39
Toru Ogawa2162.23
shunta saito3123.24
Masaki Saito4192.55