Feature-map Aggregated Salient Object Detection

Paul Vincent S. Nonat
Mark Vincent Ty
EE 298F - Advanced Deep Learning for Computer Vision
Electrical and Electronics Engineering Institute
University of the Philippines, Diliman

Our Salient Object Detection Network

Feature Aggregated Network

Loss Function

Cross Entropy Loss

IoU Loss

Fussion Loss

For BASNet evaluation and structural architecture notebook, see

https://github.com/paul028/EE298F_Final_Project/blob/master/BASNetStructEvaluation/evaluation_notebook.ipynb

Evaluation Metric

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Experiment1 - CE

a

Experiment2 - IoU

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Qualitative Result

Sample Results

Comparison with Existing Models

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Dataset Used for Training and Evaluation

Below are the Link for the dataset used in this model. Kindly site the mentioned paper if you inted to use these dataset.

DUTS Image Dataset

    @inproceedings{wang2017,
       author = {Wang, Lijun and Lu, Huchuan and Wang, Yifan and Feng, Mengyang and Wang, Dong and Yin, Baocai and Ruan, Xiang},
       title = {Learning to Detect Salient Objects With Image-Level Supervision},
       booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
       year = {2017}
    }

DUT-OMRON Image Dataset

    @inproceedings{yang2013saliency,
    title={Saliency detection via graph-based manifold ranking},
    author={Yang, Chuan and Zhang, Lihe and Lu, Huchuan, Ruan, Xiang and Yang, Ming-Hsuan},
    booktitle={Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on},
    pages={3166--3173},
    year={2013},
    organization={IEEE}
    }

Extended Complex Scene Saliency Dataset (ECSSD)
HKU-IS Dataset
PASCAL-S
SOD Dataset

Link to Presentation

You Tube Link
Slides

Link to Featuremap Prediction For all Dataset

Experiment 1
Experiment 2