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This repository provides MegEngine implementation for "Funnel Activation for Visual Recognition".

Requirement

Citation

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

@inproceedings{ma2020funnel, 
            title={Funnel activation for visual recognition},  
            author={Ma, Ningning and Zhang, Xiangyu and Sun, Jian},  
            booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},  
            year={2020} 
}

Usage

Train:

    python3 train.py --dataset-dir=/path/to/imagenet

Eval:

    python3 test.py --data=/path/to/imagenet --model /path/to/model --ngpus 1

Inference:

    python3 inference.py --model /path/to/model --image /path/to/image.jpg

Trained Models

  • OneDrive download: Link

Results

  • Comparison on ImageNet dataset:
Model Activation Top-1 err.
ResNet50 ReLU 24.0
ResNet50 PReLU 23.7
ResNet50 Swish 23.5
ResNet50 FReLU 22.4
ShuffleNetV2 0.5x ReLU 39.6
ShuffleNetV2 0.5x PReLU 39.1
ShuffleNetV2 0.5x Swish 38.7
ShuffleNetV2 0.5x FReLU 37.1