https://github.com/wanglimin/Places205-VGGNet

Places205-VGGNet models for scene recognition
https://github.com/wanglimin/Places205-VGGNet

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Places205-VGGNet models for scene recognition

• Host: GitHub
• URL: https://github.com/wanglimin/Places205-VGGNet
• Owner: wanglimin
• Created: 2015-08-06T12:48:16.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2015-12-14T21:03:26.000Z (over 8 years ago)
• Last Synced: 2024-02-28T20:36:14.460Z (4 months ago)
• Size: 11.7 KB
• Stars: 54
• Watchers: 7
• Forks: 24
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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• awesome-deeplearning-resources - VGGNets for Scene Recognition

README

        
# VGGNets for Scene Recognition

Here we release our trained VGGNet models on the large-scale Places205 dataset, called **Places205-VGGNet** models, from the following report:

http://arxiv.org/abs/1508.01667

    Places205-VGGNet Models for Scene Recognition

    Limin Wang, Sheng Guo, Weilin Huang, and Yu Qiao, in arXive 1508.01667, 2015

    

#### Performance on the Places205 dataset

|        Model        | top-1 val/test | top-5 val/test |

|:-------------------:|:--------------:|:--------------:|

| Places205-VGGNet-11 |    58.6/59.0   |    87.6/87.6   |

| Places205-VGGNet-13 |    60.2/60.1   |    88.1/88.5   |

| Places205-VGGNet-16 |    60.6/60.3   |    88.5/88.8   |

| Places205-VGGNet-19 |    61.3/61.2   |    88.8/89.3   |

We use 5 crops and their horizontal flippings of each image for testing.

#### Performance on the MIT67 and SUN397 dataset

|        Model        | MIT67 | SUN397 |

|:-------------------:|:-----:|:------:|

| Places205-VGGNet-11 |  82.0 |  65.3  |

| Places205-VGGNet-13 |  81.9 |  66.7  |

| Places205-VGGNet-16 |  81.2 |  66.9  |

We extract the fc6-layer features of our trained Places205-VGGNet models, which are further normalized by L2-norm.

#### Download

- Places205-VGGNet-11: 


  http://mmlab.siat.ac.cn/Places205-VGGNet/siat_scene_vgg_11.caffemodel

- Places205-VGGNet-13: 


  http://mmlab.siat.ac.cn/Places205-VGGNet/siat_scene_vgg_13.caffemodel

- Places205-VGGNet-16: 


  http://mmlab.siat.ac.cn/Places205-VGGNet/siat_scene_vgg_16.caffemodel

- Places205-VGGNet-19: 


  http://mmlab.siat.ac.cn/Places205-VGGNet/siat_scene_vgg_19.caffemodel

- Mean file: 


  http://mmlab.siat.ac.cn/Places205-VGGNet/places205_mean.mat

These models are relased for non-conmercial use. If you use these models in your research, thanks to cite our above report.

#### Multi-GPU Implementation

In order to speed up the training procedure of VGGNets, we use a Multi-GPU extension of Caffe toolbox:

https://github.com/yjxiong/caffe/tree/action_recog

Meanwhile, we add the strategies of _multi-scale cropping_ and _corner cropping_ provided by this extension, which has been proved to be effective for action recognition in videos.

#### Questions

Contact 

- [Limin Wang](http://wanglimin.github.io/)

- [Sheng Guo] (mailto:[email protected])

- [Weilin Huang](http://www.wlhuang.com/)