ZhaoJ9014 / Dynamic-Conditional-Networks.PyTorch

🔥🔥A pytorch implementation of Dynamic Convolutional Layer in Dynamic Conditional Convolutional Network for Few-Shot Learning🔥🔥

Dynamic Conditional Networks for Few Shot Learning

• Pytorch implementation of the algorithm in our ECCV 2018 Paper.

Getting Started

Clone the repo:

git clone https://github.com/ZhaoJ9014/Dynamic-Conditional-Networks-for-Few-Shot-Learning.pytorch.git

Requirements

Tested under python3.

• python packages
  • pytorch>=0.3.1
  • Anaconda3
• An NVIDAI GPU and CUDA 8.0 or higher. Some operations only have gpu implementation.
• NOTICE: different versions of Pytorch package have different memory usages.

Citation

• Please consult and consider citing the following paper:

  @inproceedings{zhao2018dynamic,
  title={Dynamic Conditional Networks for Few-Shot Learning},
  author={Zhao, Fang and Zhao, Jian and Yan, Shuicheng and Feng, Jiashi},
  booktitle={ECCV},
  pages={19--35},
  year={2018}
  }