This is a fork used for image reconstruction. 0. Locally Connected Layers: From pull request BVLC#3068 0. Unpool Layers: updated from old version of caffe https://github.com/HyeonwooNoh/caffe (based on original version of Caffe from January 2, 2015), which supports following architectures: 0. Deconvolution Network: Learning Deconvolution Network for Semantic Segmentation Hyeonwoo Noh, Seunghoon Hong, Bohyung Han [http://arxiv.org/abs/1505.04366] 0. Decoupled Network: Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation Seunghoon Hong, Hyeonwoo Noh, Bohyung Han [http://arxiv.org/abs/1506.04924]
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Center (BVLC) and community contributors.
Check out the project site for all the details like
- DIY Deep Learning for Vision with Caffe
- Tutorial Documentation
- BVLC reference models and the community model zoo
- Installation instructions
and step-by-step examples.
Please join the caffe-users group or gitter chat to ask questions and talk about methods and models. Framework development discussions and thorough bug reports are collected on Issues.
Happy brewing!
Caffe is released under the BSD 2-Clause license. The BVLC reference models are released for unrestricted use.
Please cite Caffe in your publications if it helps your research:
@article{jia2014caffe,
Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
Journal = {arXiv preprint arXiv:1408.5093},
Title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
Year = {2014}
}