ChainerCV: a Library for Deep Learning in Computer Vision

Yusuke Niitani, Toru Ogawa, Shunta Saito, Masaki Saito
8/28/2017
cs.CV

Official code: chainer/chainercv (1,481 stars, MIT, last commit 2021-07-01).

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.

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Code Implementations(1)

chainer/chainercvOfficial100%
MIT

ChainerCV: a Library for Deep Learning in Computer Vision

1,481291Shell, PythonFeb 13, 20175 years agoMIT
chainerchainercvcomputer-visioncupydeep-learning+2 more

Cite this paper

@article{niitani2017chainercv,
  title  = {ChainerCV: a Library for Deep Learning in Computer Vision},
  author = {Yusuke Niitani and Toru Ogawa and Shunta Saito and Masaki Saito},
  year   = {2017},
  eprint = {1708.08169},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1708.08169}
}

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