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OCOR

Bi-directional Object-context Prioritization Learning for Saliency Ranking

Install / Use

/learn @GrassBro/OCOR
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

OCOR

This is a reproduction of the CVPR'22 paper, Bi-directional Object-context Prioritization Learning for Saliency Ranking.

Installation

step 1: install pytorch and mmcv==1.3.9 referring to this.

step 2: clone this repository and execute:

python setup.py develop

step 3: install apex following this. (optional)

Dataset

Download COCO-style JSON files for the ASSR dataset from: https://pan.baidu.com/s/1XvYwBCn3sc6lAlJbJ94gUQ (pwd: ocor)

Training

bash tools/dist_train.sh configs/ocor/ocor_swin...py num_gpus 

Inference & Evaluation

python inference.py
python evaluate_SOR.py

Pre-trained Model

Download it from our Baidu cloud: https://pan.baidu.com/s/15tINLiVC8kPQm6xqxyaJlA (pwd: ocor), then use it for fine-tuning, and inference.

Results

Visual results for ASSR dataset: https://pan.baidu.com/s/1V3MzSBWI_5UNSfC1YCVf3g (pwd: ocor)

Citation

@inproceedings{tian2022bi,
  title={Bi-directional object-context prioritization learning for saliency ranking},
  author={Tian, Xin and Xu, Ke and Yang, Xin and Du, Lin and Yin, Baocai and Lau, Rynson WH},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={5882--5891},
  year={2022}
}
View on GitHub
GitHub Stars14
CategoryEducation
Updated1d ago
Forks1

Languages

Python

Security Score

90/100

Audited on Apr 2, 2026

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