Object detection with segmentation and context in deep networks
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finetuning
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model-defs
nms
segDeepM
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README.md
obtain_gpu_lock_id.m
rcnn_build.m
rcnn_config.m
rcnn_create_model.m
rcnn_extract_regions.m
rcnn_feature_stats.m
rcnn_features.m
rcnn_im_crop.m
rcnn_load_cached_pool5_features.m
rcnn_load_model.m
rcnn_pool5_to_fcX.m
rcnn_scale_features.m
startup.m

README.md

segDeepM

Object detection with segmentation and context in deep networks.

Usage

  1. Following https://github.com/rbgirshick/rcnn to set up caffe and RCNN;

  2. Fine-tune VGG/AlexNet and put the models to data/caffe_nets/ (finetuned model also available at http://www.cs.toronto.edu/~yukun/segdeepm.html)

  3. Put pre-computed CPMC masks and corresponding potentials to segDeepM/ and run segDeepM.m;

  4. Enjoy :)

citing segDeepM

Please consider citing our segDeepM paper and the original RCNN paper if you use this code for your research.

@inproceedings{ZhuSegDeepM15,
title = {segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection},
author = {Yukun Zhu and Raquel Urtasun and Ruslan Salakhutdinov and Sanja Fidler},
booktitle = {CVPR},
year = {2015}
}

@inproceedings{girshick14CVPR,
    Author = {Girshick, Ross and Donahue, Jeff and Darrell, Trevor and Malik, Jitendra},
    Title = {Rich feature hierarchies for accurate object detection and semantic segmentation},
    Booktitle = {Computer Vision and Pattern Recognition},
    Year = {2014}
}