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41a5a5eaf5
GSoC'17 Learning compact models for object detection (#1253) * Final solver and model for SqueezeNet model * update README * update dependencies and CMakeLists * add global pooling * Add training scripts * fix typo * fix dependency of caffe * fix whitespace * Add squeezedet architecture * Pascal pre process script * Adding pre process scripts * Generate the graph of the model * more readable * fix some bugs in the graph * Post process class implementation * Complete minimal post processing and standalone running * Complete the base class * remove c++11 features and fix bugs * Complete example * fix bugs * Adding final scripts * Classification scripts * Update README.md * Add example code and results * Update README.md * Re-order and fix some bugs * fix build failure * Document classes and functions * Add instructions on how to use samples * update instructionos * fix docs failure * fix conversion types * fix type conversion warning * Change examples to sample directoryu * restructure directories * add more references * fix whitespace * retain aspect ratio * Add more examples * fix docs warnings * update with links to trained weights * threshold update * png -> jpg * fix tutorial * model files * precomp.hpp , fix readme links, module dependencies * copyrights - no copyright in samples - use new style OpenCV copyright header - precomp.hpp
31 lines
1.2 KiB
BibTeX
31 lines
1.2 KiB
BibTeX
@article{SqueezeNet,
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Author = {Forrest N. Iandola and Song Han and Matthew W. Moskewicz and Khalid Ashraf and William J. Dally and Kurt Keutzer},
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Title = {SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and $<$0.5MB model size},
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Journal = {arXiv:1602.07360},
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Year = {2016}
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}
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@inproceedings{squeezedet,
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Author = {Bichen Wu and Forrest Iandola and Peter H. Jin and Kurt Keutzer},
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Title = {SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving},
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Journal = {arXiv:1612.01051},
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Year = {2016}
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}
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@inproceedings{imagenet_cvpr09,
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AUTHOR = {Deng, J. and Dong, W. and Socher, R. and Li, L.-J. and Li, K. and Fei-Fei, L.},
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TITLE = {{ImageNet: A Large-Scale Hierarchical Image Database}},
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BOOKTITLE = {CVPR09},
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YEAR = {2009},
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BIBSOURCE = "http://www.image-net.org/papers/imagenet_cvpr09.bib"}
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@Article{Everingham10,
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author = "Everingham, M. and Van~Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A.",
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title = "The Pascal Visual Object Classes (VOC) Challenge",
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journal = "International Journal of Computer Vision",
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volume = "88",
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year = "2010",
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number = "2",
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month = jun,
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pages = "303--338",
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} |