Skip to main content
SpringerLink
Log in

Group-wise co-salient object detection via multi-view self-labeling novel class discovery

  • Letter
  • Published:
Frontiers of Computer Science Aims and scope Submit manuscript

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  1. Wu Y, Song H, Liu B, Zhang K, Liu D. Co-salient object detection with uncertainty-aware group exchange-masking. In: Proceedings of 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2023, 19639–19648

  2. Fan D P, Li T, Lin Z, Ji G P, Zhang D, Cheng M M, Fu H, Shen J. Rethinking co-salient object detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 44(8): 4339–4354

    Google Scholar 

  3. Liu Y, Li T, Wu Y, Song H, Zhang K. Self-supervised image co-saliency detection. Computers and Electrical Engineering, 2023, 105: 108533

    Article  Google Scholar 

  4. Wu Y, Liang L, Zhao Y, Zhang K. Object-aware calibrated depth-guided transformer for RGB-D co-salient object detection. In: Proceedings of 2023 IEEE International Conference on Multimedia and Expo. 2023, 1121–1126

  5. Wu Y, Zhang H, Liang L, Zhao Y, Zhang K. Group-wise co-salient object detection with Siamese transformers via Brownian distance covariance matching. In: Proceedings of 2023 IEEE International Conference on Acoustics, Speech and Signal Processing. 2023, 1–5

  6. Fan Q, Fan D P, Fu H, Tang C K, Shao L, Tai Y W. Group collaborative learning for co-salient object detection. In: Proceedings of 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021, 12283–12293

  7. Fini E, Sangineto E, Lathuilière S, Zhong Z, Nabi M, Ricci E. A unified objective for novel class discovery. In: Proceedings of 2021 IEEE/CVF International Conference on Computer Vision. 2021, 9264–9272

  8. Zhang N, Han J, Liu N, Shao L. Summarize and search: learning consensus-aware dynamic convolution for co-saliency detection. In: Proceedings of 2021 IEEE/CVF International Conference on Computer Vision. 2021, 4147–4156

  9. Zhang K, Wu Y, Dong M, Liu B, Liu D, Liu Q. Deep object co-segmentation and co-saliency detection via high-order spatial-semantic network modulation. IEEE Transactions on Multimedia, 2023, 25: 5733–5746

    Article  Google Scholar 

  10. Yu S, Xiao J, Zhang B, Lim E G. Democracy does matter: comprehensive feature mining for co-salient object detection. In: Proceedings of 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2022, 969–978

Download references

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (Grant No. 62276141).

Author information

Authors and Affiliations

  1. Inspur Electronic Information Industry Co., Ltd., Beijing, 100080, China

    Yang Wu, Gang Dong, Lingyan Liang, Yaqian Zhao & Kaihua Zhang

  2. Jiangsu Key Laboratory of Big Data Analysis Technology and Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Yang Wu & Kaihua Zhang

Authors
  1. Yang Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gang Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lingyan Liang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yaqian Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kaihua Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kaihua Zhang.

Ethics declarations

Competing interests The authors declare that they have no competing interests or financial conflicts to disclose.

Electronic Supplementary Material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, Y., Dong, G., Liang, L. et al. Group-wise co-salient object detection via multi-view self-labeling novel class discovery. Front. Comput. Sci. 18, 182709 (2024). https://doi.org/10.1007/s11704-023-3284-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11704-023-3284-5

Search

Navigation