Overview of deep-learning based methods for salient object detection in videos

Qiong Wang (1, 2) , Lu Zhang (2) , Yan Li (3) , Kidiyo Kpalma (2)

1 Zhejiang University of Technology
2 IETR - Institut d'Électronique et des Technologies du numéRique
3 ULB - Université libre de Bruxelles

Video salient object detection is a challenging and important problem in computer vision domain. In recent years, deep-learning based methods have contributed to significant improvements in this domain. This paper provides an overview of recent developments in this domain and compares the corresponding methods up to date, including 1) Classification of the state-of-the-art methods and their frameworks; 2) summary of the benchmark datasets and commonly used evaluation metrics; 3) experimental comparison of the performances of the state-of-the-art methods; 4) suggestions of some promising future works for unsolved challenges.

Mots clés: Deep-learning; Salient object detection; Video

Domaines: Sciences de l'ingénieur [physics]

Qiong Wang, Lu Zhang, Yan Li, Kidiyo Kpalma. Overview of deep-learning based methods for salient object detection in videos. Pattern Recognition, 2020, 104, pp.107340. ⟨10.1016/j.patcog.2020.107340⟩. ⟨hal-02796892⟩