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Motion-Guided-CRN

This is a PyTorch implementation of Cascaded Refinement Network described in

Ping Hu, Gang Wang, Xiangfei Kong , Jason Kuen, Yap-Peng Tan;. "Motion-Guided Cascaded Refinement Network for Video Object Segmentation." CVPR, 2018

Results on DAVIS2016 can be download here

Prerequisites

  1. PyTorch
  2. Opencv

Pretraining on Pascal_VOC

  1. Edit img_path, gt_path, list_path in the file ./CRN_Pascal_Pretrain/config/CRN_Pascal.cfg.
  2. Edit file ./CRN_Pascal_Pretrain/train.sh.
  3. Run sh train.sh.

Pretraining on the DAVIS16 Training Split

  1. Edit img_path, gt_path, list_path in the file ./CRN_DAVIS16_Pretrain/config/CRN_DAVIS16.cfg.
  2. Copy a Pascal-pretrained model to ./CRN_DAVIS16_Pretrain/trained_model/.
  3. Edit file ./CRN_DAVIS16_Pretrain/train.sh.
  4. Run sh train.sh.

Online Finetuning

  1. Edit img_path, gt_path, list_path in the file ./CRN_DAVIS16_Oneshot/config/CRN_DAVIS16.cfg.
  2. Copy a DAVIS16-pretrained model to ./CRN_DAVIS16_Oneshot/trained_model/.
  3. Edit file ./CRN_DAVIS16_Pretrain/train.sh.
  4. Run sh train.sh.

Bibtex

@InProceedings{Hu_2018_CVPR,

author = {Hu, Ping and Wang, Gang and Kong , Xiangfei and Kuen, Jason and Tan, Yap-Peng},

title = {Motion-Guided Cascaded Refinement Network for Video Object Segmentation},

booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},

year = {2018}

}

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PyTorch implementation of Motion-Guided-CRN

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