Code of our paper "Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning"

Chenhongyi Yang

Last update: Dec 13, 2022

Related tags

Deep Learning CCOP

Overview

CCOP

Code of our paper Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning

Requirement

Install OpenSelfSup
Install Detectron2, Do not forget to setup Detectron2 datasets!!!
Install Kornia for fast data augmentation

Usage

Run Selective Search

% remember to setup the dataset paths
python tools/selective_search.py

Setup dataset

mkdir data
ln -s path_to_coco data

Run CCOP pre-training and Mask R-CNN benchmark

% training a ResNet-50 model with 8 GPU
zsh tools/det_train_benchmark.sh configs/selfsup/ccop/r50_d2.py 8 path_to_output

Citation

@article{yang2021contrastive,
  title={Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning},
  author={Yang, Chenhongyi and Huang, Lichao and Crowley, Elliot J},
  journal={arXiv preprint arXiv:2111.13651},
  year={2021}
}

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Comments

One missing configuration setting

Thanks for your great work and releasing the code!

During reproducing the experimental results, I noticed a tiny discrepancy between your code and the standard Mask R-CNN fine-tuning:

In your configuration file benchmarks/detection/configs/coco_R_50_FPN_1x_infomin.yaml, the configuration MODEL.ROI_BOX_HEAD.POOLER_RESOLUTION is not set. As a result, Detectron2 will use the default setting MODEL.ROI_BOX_HEAD.POOLER_RESOLUTION = 14, from https://github.com/facebookresearch/detectron2/blob/main/detectron2/config/defaults.py. However, this does not match the standard Mask R-CNN setting MODEL.ROI_BOX_HEAD.POOLER_RESOLUTION = 7. Please see https://github.com/facebookresearch/detectron2/blob/main/configs/Base-RCNN-FPN.yaml.

I'm not sure which Detectron2 version you were previously using, so this difference could be a result of Detectron2 updates as well.

opened by Friedrich1006 2

Owner

Chenhongyi Yang

Ph.D. student at the University of Edinburgh.

GitHub

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Code of our paper "Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning"

Related tags

Overview

CCOP

Requirement

Usage

Run Selective Search

Setup dataset

Run CCOP pre-training and Mask R-CNN benchmark

Citation

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