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A brief survey of visual saliency detection

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Abstract

Salient object detection models mimic the behavior of human beings and capture the most salient region/object from the images or scenes, this field contains many important applications in both computer vision and pattern recognition tasks. Despite hundreds of models that have been proposed in this field, but still, it requires a large room for research. This paper demonstrates a detailed overview of the recent progress of saliency detection models in terms of heuristic-based techniques and deep learning-based techniques. we have discussed and reviewed its co-related fields, such as Eye-fixation-prediction, RGBD salient-object-detection, co-saliency object detection, and video-saliency-detection models. We have reviewed the key issues of the current saliency models and discussed future trends and recommendations. The broadly utilized datasets and assessment strategies are additionally investigated in this paper.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China (61876098, 61976123, 61601427); National Key R&D Program of China (2018YFC0830100, 2018YFC0830102); Royal Society-K. C. Wong International Fellowship (NIF\R1\180909); Taishan Young Scholars Program of Shandong Province.

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  1. School of Software Engineering, Shandong University, Jinan, China

    Inam Ullah, Sumaira Hussain, Jie Guo & Yilong Yin

  2. School of Information Science and Engineering, Linyi University, Linyi, China

    Muwei Jian

  3. School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, China

    Muwei Jian

  4. Department of Computer Science, Sindh Madressatul Islam University, Karachi, 74000, Pakistan

    Muwei Jian & Sumaira Hussain

  5. School of Creative Technologies, University of Portsmouth, Portsmouth, UK

    Hui Yu

  6. School of Electronic and Information Engineering, Liaoning Technical University, Huludao, China

    Xing Wang

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  1. Inam Ullah
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Ullah, I., Jian, M., Hussain, S. et al. A brief survey of visual saliency detection. Multimed Tools Appl 79, 34605–34645 (2020). https://doi.org/10.1007/s11042-020-08849-y

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