GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing
Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian, Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi, Zhang, Zhongyue Zhang, Shuai Zheng, Yi Zhu

TL;DR
GluonCV and GluonNLP are comprehensive deep learning toolkits for computer vision and NLP, offering pre-trained models, flexible APIs, and cross-platform deployment to accelerate research and development.
Contribution
Introduction of modular, open-source toolkits based on MXNet that facilitate rapid prototyping, customization, and reproducible research in computer vision and NLP.
Findings
Provision of state-of-the-art pre-trained models
Flexible APIs for customization
Cross-platform deployment capabilities
Abstract
We present GluonCV and GluonNLP, the deep learning toolkits for computer vision and natural language processing based on Apache MXNet (incubating). These toolkits provide state-of-the-art pre-trained models, training scripts, and training logs, to facilitate rapid prototyping and promote reproducible research. We also provide modular APIs with flexible building blocks to enable efficient customization. Leveraging the MXNet ecosystem, the deep learning models in GluonCV and GluonNLP can be deployed onto a variety of platforms with different programming languages. The Apache 2.0 license has been adopted by GluonCV and GluonNLP to allow for software distribution, modification, and usage.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMultimodal Machine Learning Applications · Advanced Neural Network Applications · COVID-19 diagnosis using AI
