{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:38:40Z","timestamp":1740123520582,"version":"3.37.3"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2022,8,6]],"date-time":"2022-08-06T00:00:00Z","timestamp":1659744000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,8,6]],"date-time":"2022-08-06T00:00:00Z","timestamp":1659744000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Comput Vis"],"published-print":{"date-parts":[[2022,10]]},"DOI":"10.1007\/s11263-022-01655-z","type":"journal-article","created":{"date-parts":[[2022,8,6]],"date-time":"2022-08-06T16:02:45Z","timestamp":1659801765000},"page":"2408-2424","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Exploring the Semi-Supervised Video Object Segmentation Problem from a Cyclic Perspective"],"prefix":"10.1007","volume":"130","author":[{"given":"Yuxi","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ning","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjie","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"See","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8307-7107","authenticated-orcid":false,"given":"Weiyao","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,8,6]]},"reference":[{"key":"1655_CR1","doi-asserted-by":"crossref","unstructured":"Bansal A, Ma S, Ramanan D, & Sheikh Y (2018) Recycle-gan: unsupervised video retargeting. In: European conference on computer vision (ECCV)","DOI":"10.1007\/978-3-030-01228-1_8"},{"key":"1655_CR2","doi-asserted-by":"crossref","unstructured":"Caelles S., Maninis, K.K., Pont-Tuset, J., Leal-Taix\u00e9, L., Cremers, D., & Van Gool, L. (2017). One-shot video object segmentation. In: Computer Vision and Pattern Recognition (CVPR)","DOI":"10.1109\/CVPR.2017.565"},{"key":"1655_CR3","unstructured":"Carl, V., Abhinav, S., Alireza, F., Sergio, G., & Kevin, M. (2018). Tracking emerges by colorizing videos. European Conference on Computer Vision"},{"key":"1655_CR4","doi-asserted-by":"crossref","unstructured":"Dong, Y., Liao, F., Pang, T., Su, H., Zhu, J., Hu, X., & Li, J. (2018). Boosting adversarial attacks with momentum. In: Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR), pp. 9185\u20139193","DOI":"10.1109\/CVPR.2018.00957"},{"issue":"1","key":"1655_CR5","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1007\/s11263-014-0733-5","volume":"111","author":"M Everingham","year":"2015","unstructured":"Everingham, M., Eslami, S. M. A., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman, A. (2015). The pascal visual object classes challenge: A retrospective. International Journal of Computer Vision (IJCV), 111(1), 98\u2013136.","journal-title":"International Journal of Computer Vision (IJCV)"},{"key":"1655_CR6","unstructured":"Goodfellow, I.J., Shlens, J., & Szegedy, C. (2014). Explaining and harnessing adversarial examples. arXiv preprint arXiv:1412.6572"},{"key":"1655_CR7","doi-asserted-by":"crossref","unstructured":"He, K., Georgia, G., Piotr, D., & Ross, G. (2018). Mask r-cnn. In: international conference on computer vision (ICCV)","DOI":"10.1109\/ICCV.2017.322"},{"key":"1655_CR8","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In: The IEEE conference on computer vision and pattern recognition (CVPR)","DOI":"10.1109\/CVPR.2016.90"},{"key":"1655_CR9","unstructured":"Jabri, A., Owens, A., & Efros, A.A. (2020). Space-time correspondence as a contrastive random walk. Advances in Neural Information Processing Systems"},{"key":"1655_CR10","doi-asserted-by":"crossref","unstructured":"Johnander, J., Danelljan, M., Brissman, E., Khan, F.S., & Felsberg, M. (2019). A generative appearance model for end-to-end video object segmentation. In: IEEE\/CVF conference on computer vision and pattern recognition (CVPR), pp. 8953\u20138962","DOI":"10.1109\/CVPR.2019.00916"},{"key":"1655_CR11","doi-asserted-by":"publisher","first-page":"1175","DOI":"10.1007\/s11263-019-01164-6","volume":"127","author":"A Khoreva","year":"2019","unstructured":"Khoreva, A., Benenson, R., Ilg, E., Brox, T., & Schiele, B. (2019). Lucid data dreaming for video object segmentation. International Journal of Computer Vision (IJCV), 127, 1175\u20131197.","journal-title":"International Journal of Computer Vision (IJCV)"},{"key":"1655_CR12","unstructured":"Kingma, D.P., & Ba, J. (2014). Adam: A method for stochastic optimization. In: international conference on learning representation (ICLR)"},{"key":"1655_CR13","doi-asserted-by":"crossref","unstructured":"Li, Y., Shen, Z., & Shan, Y. (2020). Fast video object segmentation using the global context module. In: European conference on computer vision (ECCV), pp. 735\u2013750","DOI":"10.1007\/978-3-030-58607-2_43"},{"key":"1655_CR14","unstructured":"Li, Y., Xu, N., Jinlong, P., See, J., & Weiyao, L. (2020). Delving into the cyclic mechanism in semi-supervised video object segmentation. In: Neural Information Processing System (NeurIPS)"},{"key":"1655_CR15","doi-asserted-by":"crossref","unstructured":"Lin, H., Qi, X., & Jia, J. (2019). Agss-vos: Attention guided single-shot video object segmentation. In: The IEEE international conference on computer vision (ICCV)","DOI":"10.1109\/ICCV.2019.00405"},{"key":"1655_CR16","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Doll\u00e1r, P., & Zitnick, C.L. (2014). Microsoft coco: Common objects in context. In: European conference on computer vision (ECCV). Z\u00fcrich","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"1655_CR17","doi-asserted-by":"crossref","unstructured":"Luiten, J., Voigtlaender, P., & Leibe, B. (2018). Premvos: Proposal-generation, refinement and merging for video object segmentation. In: Asian conference on computer vision (ACCV)","DOI":"10.1007\/978-3-030-20870-7_35"},{"key":"1655_CR18","doi-asserted-by":"crossref","unstructured":"Meister, S., Hur, J., & Roth, S. (2018). UnFlow: Unsupervised learning of optical flow with a bidirectional census loss. In: AAAI. New Orleans, Louisiana","DOI":"10.1609\/aaai.v32i1.12276"},{"key":"1655_CR19","doi-asserted-by":"crossref","unstructured":"Oh, S.W., Lee, J.Y., Xu, N., & Kim, S.J. (2019). Video object segmentation using space-time memory networks. In: The IEEE international conference on computer vision (ICCV)","DOI":"10.1109\/ICCV.2019.00932"},{"key":"1655_CR20","doi-asserted-by":"crossref","unstructured":"Peng, J., Wang, C., Wan, F., Wu, Y., Wang, Y., Tai, Y., Wang, C., Li, J., Huang, F., & Fu, Y. (2020). Chained-tracker: Chaining paired attentive regression results for end-to-end joint multiple-object detection and tracking. In: The European conference on computer vision (ECCV)","DOI":"10.1007\/978-3-030-58548-8_9"},{"key":"1655_CR21","unstructured":"Pretraining code of space-time-memory network on coco for video object segmentation. https:\/\/github.com\/haochenheheda\/Training-Code-of-STM"},{"key":"1655_CR22","doi-asserted-by":"crossref","unstructured":"Perazzi, F., Khoreva, A., Benenson, R., Schiele, B., & Sorkine-Hornung, A. (2017). Learning video object segmentation from static images. In: The IEEE conference on computer vision and pattern recognition (CVPR)","DOI":"10.1109\/CVPR.2017.372"},{"key":"1655_CR23","doi-asserted-by":"crossref","unstructured":"Perazzi, F., Pont-Tuset, J., McWilliams, B., Van Gool, L., Gross, M., & Sorkine-Hornung, A. (2016). A benchmark dataset and evaluation methodology for video object segmentation. In: computer vision and pattern recognition (CVPR)","DOI":"10.1109\/CVPR.2016.85"},{"key":"1655_CR24","unstructured":"Pont-Tuset, J., Perazzi, F., Caelles, S., Arbel\u00e1ez, P., Sorkine-Hornung, A., & Van Gool, L. (2017). The 2017 davis challenge on video object segmentation. arXiv:1704.00675"},{"key":"1655_CR25","doi-asserted-by":"crossref","unstructured":"Robinson, A., Lawin, F.J., Danelljan, M., Khan, F.S., & Felsberg, M. (2020). Learning fast and robust target models for video object segmentation. In: IEEE\/CVF conference on computer vision and pattern recognition (CVPR)","DOI":"10.1109\/CVPR42600.2020.00743"},{"issue":"3","key":"1655_CR26","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A. C., & Fei-Fei, L. (2015). Imagenet large scale visual recognition challenge. International Journal of Computer Vision (IJCV), 115(3), 211\u2013252.","journal-title":"International Journal of Computer Vision (IJCV)"},{"key":"1655_CR27","doi-asserted-by":"crossref","unstructured":"Seong, H., Hyun, J., & Kim, E. (2020). Kernelized memory network for video object segmentation. In: European conference on computer vision (ECCV), pp. 629\u2013645","DOI":"10.1007\/978-3-030-58542-6_38"},{"issue":"4","key":"1655_CR28","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1109\/TPAMI.2015.2465960","volume":"38","author":"J Shi","year":"2016","unstructured":"Shi, J., Yan, Q., Xu, L., & Jia, J. (2016). Hierarchical image saliency detection on extended cssd. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 38(4), 717\u2013729.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)"},{"key":"1655_CR29","unstructured":"Tinghui, Z., Philipp, K., Mathieu, A., Qixing, H., & Alexei, A.E. (2016). Learning dense correspondence via 3d-guided cycle consistency. The IEEE conference on computer vision and pattern recognition (CVPR)"},{"key":"1655_CR30","doi-asserted-by":"crossref","unstructured":"Ventura, C., Bellver, M., Girbau, A., Salvador, A., Marques, F., & Giro-i Nieto, X. (2019). Rvos: End-to-end recurrent network for video object segmentation. In: The IEEE conference on computer vision and pattern recognition (CVPR)","DOI":"10.1109\/CVPR.2019.00542"},{"key":"1655_CR31","doi-asserted-by":"crossref","unstructured":"Voigtlaender, P., Chai, Y., Schroff, F., Adam, H., Leibe, B., & Chen, L.C. (2019). Feelvos: Fast end-to-end embedding learning for video object segmentation. In: The IEEE conference on computer vision and pattern recognition (CVPR)","DOI":"10.1109\/CVPR.2019.00971"},{"key":"1655_CR32","doi-asserted-by":"crossref","unstructured":"Voigtlaender, P., & Leibe, B. (2017). Online adaptation of convolutional neural networks for video object segmentation. In: British machine vision conference (BMVC)","DOI":"10.5244\/C.31.116"},{"key":"1655_CR33","doi-asserted-by":"crossref","unstructured":"Wang, X., Jabri, A., & Efros, A.A. (2019). Learning correspondence from the cycle-consistency of time. In: The IEEE conference on computer vision and pattern recognition (CVPR)","DOI":"10.1109\/CVPR.2019.00267"},{"key":"1655_CR34","doi-asserted-by":"crossref","unstructured":"Wug\u00a0Oh, S., Lee, J.Y., Sunkavalli, K., & Joo\u00a0Kim, S. (2018). Fast video object segmentation by reference-guided mask propagation. In: The IEEE conference on computer vision and pattern recognition (CVPR)","DOI":"10.1109\/CVPR.2018.00770"},{"key":"1655_CR35","doi-asserted-by":"crossref","unstructured":"Xu, N., Yang, L., Fan, Y., Yang, J., Yue, D., Liang, Y., Price, B., Cohen, S., & Huang, T. (2018). Youtube-vos: Sequence-to-sequence video object segmentation. In: the European conference on computer vision (ECCV)","DOI":"10.1007\/978-3-030-01228-1_36"},{"key":"1655_CR36","unstructured":"Yang, Z., Wei, Y., & Yang, Y. (2021). Associating objects with transformers for video object segmentation. Advances in Neural Information Processing Systems, 34, 2491\u20132502."},{"key":"1655_CR37","doi-asserted-by":"crossref","unstructured":"Zeng, X., Liao, R., Gu, L., Xiong, Y., Fidler, S., & Urtasun, R. (2019). Dmm-net: Differentiable mask-matching network for video object segmentation. In: The IEEE international conference on computer vision (ICCV)","DOI":"10.1109\/ICCV.2019.00403"},{"key":"1655_CR38","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Wu, Z., Peng, H., & Lin, S. (2020). A transductive approach for video object segmentation. In: proceedings of the IEEE conference on computer vision and pattern recognition","DOI":"10.1109\/CVPR42600.2020.00698"},{"key":"1655_CR39","doi-asserted-by":"crossref","unstructured":"Zhu, J.Y., Park, T., Isola, P., & Efros, A.A. (2017). Unpaired image-to-image translation using cycle-consistent adversarial networks. In: IEEE international conference on computer vision (ICCV)","DOI":"10.1109\/ICCV.2017.244"}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-022-01655-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11263-022-01655-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-022-01655-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T21:57:10Z","timestamp":1727733430000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11263-022-01655-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,6]]},"references-count":39,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2022,10]]}},"alternative-id":["1655"],"URL":"https:\/\/doi.org\/10.1007\/s11263-022-01655-z","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"type":"print","value":"0920-5691"},{"type":"electronic","value":"1573-1405"}],"subject":[],"published":{"date-parts":[[2022,8,6]]},"assertion":[{"value":"31 October 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 July 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 August 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}