DeepMark: One-Shot Clothing Detection

Alexey Sidnev, Alexey Trushkov, Maxim Kazakov, Ivan Korolev, Vladislav Sorokin

ICCVW 2019 pp. 3201-3204

doi:10.1109/ICCVW.2019.00399 /iccvw/2019/sidnev2019iccvw-deepmark/

Abstract

The one-shot approach, DeepMark, for fast clothing detection as a modification of a multi-target network, CenterNet, is proposed in the paper. The state-of-the-art accuracy of 0.723 mAP for bounding box detection task and 0.532 mAP for landmark detection task on the DeepFashion2 Challenge dataset were achieved. The proposed architecture can be used effectively on the low-power devices.

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Text

Sidnev et al. "DeepMark: One-Shot Clothing Detection." IEEE/CVF International Conference on Computer Vision Workshops, 2019. doi:10.1109/ICCVW.2019.00399

Markdown

[Sidnev et al. "DeepMark: One-Shot Clothing Detection." IEEE/CVF International Conference on Computer Vision Workshops, 2019.](https://mlanthology.org/iccvw/2019/sidnev2019iccvw-deepmark/) doi:10.1109/ICCVW.2019.00399

BibTeX

@inproceedings{sidnev2019iccvw-deepmark,
  title     = {{DeepMark: One-Shot Clothing Detection}},
  author    = {Sidnev, Alexey and Trushkov, Alexey and Kazakov, Maxim and Korolev, Ivan and Sorokin, Vladislav},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2019},
  pages     = {3201-3204},
  doi       = {10.1109/ICCVW.2019.00399},
  url       = {https://mlanthology.org/iccvw/2019/sidnev2019iccvw-deepmark/}
}