{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T16:14:25Z","timestamp":1770394465978,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":27,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819557578","type":"print"},{"value":"9789819557585","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-981-95-5758-5_36","type":"book-chapter","created":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T05:00:25Z","timestamp":1770354025000},"page":"501-516","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Unsupervised Salient Object Detection via\u00a0Contrastive Learning and\u00a0UnSAM"],"prefix":"10.1007","author":[{"given":"Tongtong","family":"Gao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Ye","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianlong","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoming","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,2,7]]},"reference":[{"key":"36_CR1","doi-asserted-by":"crossref","unstructured":"Caron, M., et al.: Emerging properties in self-supervised vision transformers. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9650\u20139660 (2021)","DOI":"10.1109\/ICCV48922.2021.00951"},{"key":"36_CR2","doi-asserted-by":"crossref","unstructured":"Gao, S., Xing, H., Zhang, W., Wang, Y., Guo, Q., Zhang, W.: Weakly supervised video salient object detection via point supervision. In: Proceedings of the 30th ACM International Conference on Multimedia, pp. 3656\u20133665 (2022)","DOI":"10.1145\/3503161.3547912"},{"key":"36_CR3","doi-asserted-by":"publisher","first-page":"2487","DOI":"10.1109\/TIP.2025.3558674","volume":"34","author":"H Guan","year":"2025","unstructured":"Guan, H., Lin, J., Lau, R.W.H.: A contrastive-learning framework for unsupervised salient object detection. IEEE Trans. Image Process. 34, 2487\u20132498 (2025)","journal-title":"IEEE Trans. Image Process."},{"key":"36_CR4","doi-asserted-by":"crossref","unstructured":"He, J., Fu, K., Liu, X., Zhao, Q.: Samba: a unified mamba-based framework for general salient object detection. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 25314\u201325324 (2025)","DOI":"10.1109\/CVPR52734.2025.02357"},{"key":"36_CR5","doi-asserted-by":"crossref","unstructured":"Jiang, B., Zhang, L., Lu, H., Yang, C., Yang, M.H.: Saliency detection via absorbing Markov chain. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1665\u20131672 (2013)","DOI":"10.1109\/ICCV.2013.209"},{"key":"36_CR6","doi-asserted-by":"crossref","unstructured":"Li, G., Xie, Y., Lin, L.: Weakly supervised salient object detection using image labels. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 32 (2018)","DOI":"10.1609\/aaai.v32i1.12308"},{"key":"36_CR7","doi-asserted-by":"crossref","unstructured":"Luo, Z., et al.: VSCode: general visual salient and camouflaged object detection with 2D prompt learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 17169\u201317180 (2024)","DOI":"10.1109\/CVPR52733.2024.01625"},{"key":"36_CR8","doi-asserted-by":"crossref","unstructured":"Piao, Y., Wang, J., Zhang, M., Lu, H.: MFNet: multi-filter directive network for weakly supervised salient object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4136\u20134145 (2021)","DOI":"10.1109\/ICCV48922.2021.00410"},{"key":"36_CR9","doi-asserted-by":"publisher","first-page":"2888","DOI":"10.1109\/TMM.2022.3152567","volume":"25","author":"Y Piao","year":"2022","unstructured":"Piao, Y., Wu, W., Zhang, M., Jiang, Y., Lu, H.: Noise-sensitive adversarial learning for weakly supervised salient object detection. IEEE Trans. Multimedia 25, 2888\u20132897 (2022)","journal-title":"IEEE Trans. Multimedia"},{"key":"36_CR10","doi-asserted-by":"crossref","unstructured":"Qin, X., Zhang, Z., Huang, C., Gao, C., Jagersand, M.: BASNet: boundary-aware salient object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7479\u20137489 (2019)","DOI":"10.1109\/CVPR.2019.00766"},{"key":"36_CR11","doi-asserted-by":"crossref","unstructured":"Sim\u00e9oni, O., Sekkat, C., Puy, G., Vobeck\u1ef3, A., Zablocki, \u00c9., P\u00e9rez, P.: Unsupervised object localization: observing the background to discover objects. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3176\u20133186 (2023)","DOI":"10.1109\/CVPR52729.2023.00310"},{"key":"36_CR12","doi-asserted-by":"crossref","unstructured":"Wang, L., et al.: Learning to detect salient objects with image-level supervision. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 136\u2013145 (2017)","DOI":"10.1109\/CVPR.2017.404"},{"key":"36_CR13","doi-asserted-by":"crossref","unstructured":"Wang, X., Girdhar, R., Yu, S.X., Misra, I.: Cut and learn for unsupervised object detection and instance segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3124\u20133134 (2023)","DOI":"10.1109\/CVPR52729.2023.00305"},{"key":"36_CR14","unstructured":"Wang, X., Yang, J., Darrell, T.: Segment anything without supervision. In: The Thirty-Eighth Annual Conference on Neural Information Processing Systems (2024)"},{"key":"36_CR15","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wang, R., Fan, X., Wang, T., He, X.: Pixels, regions, and objects: multiple enhancement for salient object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10031\u201310040 (2023)","DOI":"10.1109\/CVPR52729.2023.00967"},{"key":"36_CR16","doi-asserted-by":"publisher","first-page":"110579","DOI":"10.1016\/j.patcog.2024.110579","volume":"154","author":"Y Wang","year":"2024","unstructured":"Wang, Y., et al.: WBNet: weakly-supervised salient object detection via scribble and pseudo-background priors. Pattern Recogn. 154, 110579 (2024)","journal-title":"Pattern Recogn."},{"key":"36_CR17","doi-asserted-by":"crossref","unstructured":"Xie, J., Xiang, J., Chen, J., Hou, X., Zhao, X., Shen, L.: C2AM: contrastive learning of class-agnostic activation map for weakly supervised object localization and semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 989\u2013998 (2022)","DOI":"10.1109\/CVPR52688.2022.00106"},{"key":"36_CR18","doi-asserted-by":"crossref","unstructured":"Yan, Q., Xu, L., Shi, J., Jia, J.: Hierarchical saliency detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1155\u20131162 (2013)","DOI":"10.1109\/CVPR.2013.153"},{"key":"36_CR19","doi-asserted-by":"crossref","unstructured":"Yasarla, R., Weng, R., Choi, W., Patel, V.M., Sadeghian, A.: 3SD: self-supervised saliency detection with no labels. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 313\u2013322 (2024)","DOI":"10.1109\/WACV57701.2024.00038"},{"key":"36_CR20","doi-asserted-by":"crossref","unstructured":"Yu, S., Zhang, B., Xiao, J., Lim, E.G.: Structure-consistent weakly supervised salient object detection with local saliency coherence. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a035, pp. 3234\u20133242 (2021)","DOI":"10.1609\/aaai.v35i4.16434"},{"key":"36_CR21","doi-asserted-by":"crossref","unstructured":"Zeng, Y., Zhuge, Y., Lu, H., Zhang, L., Qian, M., Yu, Y.: Multi-source weak supervision for saliency detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6074\u20136083 (2019)","DOI":"10.1109\/CVPR.2019.00623"},{"key":"36_CR22","doi-asserted-by":"crossref","unstructured":"Zhang, J., Yu, X., Li, A., Song, P., Liu, B., Dai, Y.: Weakly-supervised salient object detection via scribble annotations. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12546\u201312555 (2020)","DOI":"10.1109\/CVPR42600.2020.01256"},{"key":"36_CR23","doi-asserted-by":"crossref","unstructured":"Zhang, J., Zhang, T., Dai, Y., Harandi, M., Hartley, R.: Deep unsupervised saliency detection: a multiple noisy labeling perspective. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 9029\u20139038 (2018)","DOI":"10.1109\/CVPR.2018.00941"},{"issue":"2","key":"36_CR24","doi-asserted-by":"publisher","first-page":"743","DOI":"10.1109\/TCSVT.2022.3203595","volume":"33","author":"H Zhou","year":"2022","unstructured":"Zhou, H., Chen, P., Yang, L., Xie, X., Lai, J.: Activation to saliency: forming high-quality labels for unsupervised salient object detection. IEEE Trans. Circ. Syst. Video Technol. 33(2), 743\u2013755 (2022)","journal-title":"IEEE Trans. Circ. Syst. Video Technol."},{"key":"36_CR25","doi-asserted-by":"crossref","unstructured":"Zhou, H., Qiao, B., Yang, L., Lai, J., Xie, X.: Texture-guided saliency distilling for unsupervised salient object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7257\u20137267 (2023)","DOI":"10.1109\/CVPR52729.2023.00701"},{"key":"36_CR26","doi-asserted-by":"crossref","unstructured":"Zhu, W., Liang, S., Wei, Y., Sun, J.: Saliency optimization from robust background detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2814\u20132821 (2014)","DOI":"10.1109\/CVPR.2014.360"},{"issue":"3","key":"36_CR27","first-page":"3738","volume":"45","author":"M Zhuge","year":"2022","unstructured":"Zhuge, M., Fan, D.P., Liu, N., Zhang, D., Xu, D., Shao, L.: Salient object detection via integrity learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(3), 3738\u20133752 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-5758-5_36","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T05:00:34Z","timestamp":1770354034000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5758-5_36"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819557578","9789819557585"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5758-5_36","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"7 February 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2025.prcv.cn\/index.asp","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}