## Pre-trained Models

We provide a number of pre-trained models for easy use. When using these models, please cite and heed licenses accordingly! We also welcome community contributions via pull requests to the repository.

You can find a number of demos showing how to download and run the models below here.

### The List

This list contains links to architecture definitions (*.json), download scripts for the mean images (*.tensor), and pre-trained weights (*.marvin). We have also taken care to give credit where it is due, so please let us know if there is anything wrong or missing.

Architecture Mean image Weights Trainer Citation License
AlexNet for ImageNet ImageNet1k Download BVLC C1 C2 C3 L1 L2 L3

### Citations

1. Jia, Yangqing, et al. "Caffe: Convolutional architecture for fast feature embedding." Proceedings of the ACM International Conference on Multimedia. 2014.
2. Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. "Imagenet classification with deep convolutional neural networks." Advances in neural information processing systems. 2012.
3. Deng, Jia, et al. "Imagenet: A large-scale hierarchical image database." IEEE Conference on Computer Vision and Pattern Recognition. 2009.
4. Zhou, Bolei, et al. "Learning deep features for scene recognition using places database." Advances in Neural Information Processing Systems. 2014.
5. Szegedy, Christian, et al. "Going deeper with convolutions." arXiv preprint arXiv:1409.4842. 2014.
6. Simonyan, Karen, and Andrew Zisserman. "Very deep convolutional networks for large-scale image recognition." arXiv preprint arXiv:1409.1556. 2014.
7. </ol>