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Data-Driven Neuron Allocation for Scale Aggregation Networks
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figures release Apr 19, 2019
pytorch release Apr 19, 2019
structures release Apr 19, 2019
tensorflow release Apr 19, 2019
.gitignore release Apr 19, 2019


By Yi Li, Zhanghui Kuang, Yimin Chen, Wayne Zhang


Table of Contents

  1. Introduction
  2. Citation
  3. Approach
  4. Trained models
  5. Experiments
  6. GPU time


This is a PyTorch implementation of Data-Driven Neuron Allocation for Scale Aggregation Networks.(CVPR2019) with pretrained models.


If you use these models in your research, please cite:

    title={Data-Driven Neuron Allocation for Scale Aggregation Networks},
    author={Li, Yi and Kuang, Zhanghui and Chen, Yimin and Zhang, Wayne},


Figure 1: architecture of ScaleNet-50.

Figure 2: scale aggregation block.

Trained models

Model Top-1 err. Top-5 err.
ScaleNet-50-light 22.80 6.57
ScaleNet-50 22.02 6.05
ScaleNet-101 20.82 5.42
ScaleNet-152 20.06 5.18


from pytorch.scalenet import *
model = scalenet50(structure_path='structures/scalenet50.json', ckpt=None) # train from stratch
model = scalenet50(structure_path='structures/scalenet50.json', ckpt='weights/scalenet50.pth') # load pretrained model

The weights are available on BaiduYun with extract code: f1c5

Unlike the paper, we used better training settings: increase the epochs to 120 and replace multi-step learning rate by cosine learning rate.


Figure 3: experiments on imagenet classification.

Figure 4: experiments on ms-coco detection.

GPU time

Model Top-1 err. FLOPs(10^9) GPU time(ms)
ResNet-50 24.02 4.1 95
SE-ResNet-50 23.29 4.1 98
ResNeXt-50 22.2 4.2 147
ScaleNet-50 22.2 3.8 93

TensorFlow: (empty models of ResNet, SE-ResNet, ResNeXt, ScaleNet for speed test)

python3 tensorflow/ scale|res|se|next

All networks were tested using Tensorflow with GTX 1060 GPU and i7 CPU at batch size 16 and image side 224 on 1000 runs.

Some static-graph frameworks like Tensorflow and TensorRT execute multi-branch models in parallel, while Pytorch and Caffe do not. So we suggest to deploy ScaleNets on Tensorflow and TensorRT.

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