PyTorch implementation of Octave Convolution in Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
| Architecture | LR decay strategy | Parameters | GFLOPs | Top-1 / Top-5 Accuracy (%) |
|---|---|---|---|---|
| ResNet-50 | step (90 epochs) | 25.557M | 4.089 | 76.010 / 92.834 |
| ResNet-50 | cosine (120 epochs) | 25.557M | 4.089 | 77.150 / 93.468 |
| OctResNet-50 (alpha=0.5) | cosine (120 epochs) | 25.557M | 2.367 | 77.640 / 93.662 |
- Support for MobileNet family (pending for architectural details from the author)
Official MXNet implmentation by @cypw
@article{chen2019drop,
title={Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution},
author={Chen, Yunpeng and Fan, Haoqi and Xu, Bing and Yan, Zhicheng and Kalantidis, Yannis and Rohrbach, Marcus and Yan, Shuicheng and Feng, Jiashi},
journal={arXiv preprint arXiv:1904.05049},
year={2019}
}