CVAug 28, 2017

ChainerCV: a Library for Deep Learning in Computer Vision

arXiv:1708.08169v154 citations
Originality Synthesis-oriented
AI Analysis

This provides a tool for researchers and practitioners in computer vision to streamline development and benchmarking, though it is incremental as it builds on existing methods.

The authors tackled the lack of a unifying software library for deep learning in computer vision by introducing ChainerCV, which supports numerous models and components, achieving performance on par with published papers.

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.

Code Implementations2 repos
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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