Funnel Activation for Visual Recognition

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

Requirement

• MegEngine 0.5.1 (https://github.com/MegEngine/MegEngine)

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