WongKinYiu/PartialResidualNetworks

Partial Residual Networks

This is the implementation of "Enriching Variety of Layer-wise Learning Information by Gradient Combination" using Darknet framwork.

Our paper will be appear in 2019 ICCV Workshop on Low-Power Computer Vision.

For installing Darknet framework, you can refer to darknet(pjreddie) or darknet(AlexeyAB).

We provide YOLO-v3-tiny-PRN cfg file and COCO pre-trained model. You can use provided files to get following results on COCO test-dev set:

We also provide cfg file and COCO pre-trained model for morden backbone EfficientNet_b0 [2]. For training this model, you should install darknet(AlexeyAB).

Here we provide some experimental results on COCO test-dev set which are not listed in the paper.

Reference

[1] Redmon, J., & Farhadi, A. (2018). Yolov3: An incremental improvement. arXiv preprint arXiv:1804.02767.

[2] Tan, M., & Le, Q. V. (2019). EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. arXiv preprint arXiv:1905.11946.

[3] Wang, R. J., Li, X., & Ling, C. X. (2018). Pelee: A real-time object detection system on mobile devices. In Advances in Neural Information Processing Systems (pp. 1963-1972).

[4] Lin, T. Y., Dollár, P., Girshick, R., He, K., Hariharan, B., & Belongie, S. (2017). Feature pyramid networks for object detection. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2117-2125).

Acknowledgements

https://github.com/AlexeyAB/darknet