{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T03:00:43Z","timestamp":1770346843544,"version":"3.49.0"},"publisher-location":"Cham","reference-count":37,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030110239","type":"print"},{"value":"9783030110246","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-11024-6_55","type":"book-chapter","created":{"date-parts":[[2019,1,24]],"date-time":"2019-01-24T04:29:27Z","timestamp":1548304167000},"page":"715-730","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["MoA-Net: Self-supervised Motion Segmentation"],"prefix":"10.1007","author":[{"given":"Pia","family":"Bideau","sequence":"first","affiliation":[]},{"given":"Rakesh R.","family":"Menon","sequence":"additional","affiliation":[]},{"given":"Erik","family":"Learned-Miller","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,1,23]]},"reference":[{"key":"55_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1007\/978-3-319-46484-8_26","volume-title":"Computer Vision \u2013 ECCV 2016","author":"Pia Bideau","year":"2016","unstructured":"Bideau, Pia, Learned-Miller, Erik: It\u2019s moving! A probabilistic model for causal motion segmentation in moving camera videos. In: Leibe, Bastian, Matas, Jiri, Sebe, Nicu, Welling, Max (eds.) ECCV 2016. LNCS, vol. 9912, pp. 433\u2013449. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46484-8_26"},{"key":"55_CR2","doi-asserted-by":"crossref","unstructured":"Bideau, P., RoyChowdhury, A., Menon, R.R., Learned-Miller, E.: The best of both worlds: combining CNNs and geometric constraints for hierarchical motion segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 508\u2013517 (2018)","DOI":"10.1109\/CVPR.2018.00060"},{"key":"55_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1007\/978-3-642-15555-0_21","volume-title":"Computer Vision \u2013 ECCV 2010","author":"Thomas Brox","year":"2010","unstructured":"Brox, Thomas, Malik, Jitendra: Object segmentation by long term analysis of point trajectories. In: Daniilidis, Kostas, Maragos, Petros, Paragios, Nikos (eds.) ECCV 2010. LNCS, vol. 6315, pp. 282\u2013295. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-15555-0_21"},{"issue":"3","key":"55_CR4","doi-asserted-by":"publisher","first-page":"500","DOI":"10.1109\/TPAMI.2010.143","volume":"33","author":"T Brox","year":"2011","unstructured":"Brox, T., Malik, J.: Large displacement optical flow: descriptor matching in variational motion estimation. IEEE Trans. Pattern Anal. Mach. Intell. 33(3), 500\u2013513 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"55_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1007\/978-3-642-33783-3_44","volume-title":"Computer Vision \u2013 ECCV 2012","author":"Daniel J Butler","year":"2012","unstructured":"Butler, Daniel J., Wulff, Jonas, Stanley, Garrett B., Black, Michael J.: A naturalistic open source movie for optical flow evaluation. In: Fitzgibbon, Andrew, Lazebnik, Svetlana, Perona, Pietro, Sato, Yoichi, Schmid, Cordelia (eds.) ECCV 2012. LNCS, vol. 7577, pp. 611\u2013625. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33783-3_44"},{"issue":"1\u20133","key":"55_CR6","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/0004-3702(81)90024-2","volume":"17","author":"BK Horn","year":"1981","unstructured":"Horn, B.K., Schunck, B.G.: Determining optical flow. Artif. Intell. 17(1\u20133), 185\u2013203 (1981)","journal-title":"Artif. Intell."},{"key":"55_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1007\/978-3-319-46604-0_12","volume-title":"Computer Vision \u2013 ECCV 2016 Workshops","author":"Junhwa Hur","year":"2016","unstructured":"Hur, Junhwa, Roth, Stefan: Joint optical flow and temporally consistent semantic segmentation. In: Hua, Gang, J\u00e9gou, Herv\u00e9 (eds.) ECCV 2016. LNCS, vol. 9913, pp. 163\u2013177. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46604-0_12"},{"key":"55_CR8","doi-asserted-by":"crossref","unstructured":"Irani, M., Anandan, P.: A unified approach to moving object detection in 2D and 3D scenes. 20(6), 577\u2013589 (1998)","DOI":"10.1109\/34.683770"},{"key":"55_CR9","doi-asserted-by":"crossref","unstructured":"Jain, S., Xiong, B., Grauman, K.: Fusionseg: learning to combine motion and appearance for fully automatic segmention of generic objects in videos. In: CVPR (2017)","DOI":"10.1109\/CVPR.2017.228"},{"key":"55_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"656","DOI":"10.1007\/978-3-319-10593-2_43","volume-title":"Computer Vision \u2013 ECCV 2014","author":"Suyog Dutt Jain","year":"2014","unstructured":"Jain, Suyog Dutt, Grauman, Kristen: Supervoxel-consistent foreground propagation in video. In: Fleet, David, Pajdla, Tomas, Schiele, Bernt, Tuytelaars, Tinne (eds.) ECCV 2014. LNCS, vol. 8692, pp. 656\u2013671. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10593-2_43"},{"issue":"4","key":"55_CR11","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1007\/s003590050393","volume":"185","author":"MF Land","year":"1999","unstructured":"Land, M.F.: Motion and vision: why animals move their eyes. J. Comp. Physiol. A 185(4), 341\u2013352 (1999)","journal-title":"J. Comp. Physiol. A"},{"key":"55_CR12","doi-asserted-by":"crossref","unstructured":"Lappe, M., Hoffmann, K.P., et al.: Optic flow and eye movements. Int. Rev. Neurobiol. 29\u201350 (2000)","DOI":"10.1016\/S0074-7742(08)60736-9"},{"key":"55_CR13","doi-asserted-by":"crossref","unstructured":"Li, F., Kim, T., Humayun, A., Tsai, D., Rehg, J.M.: Video segmentation by tracking many figure-ground segments. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2192\u20132199 (2013)","DOI":"10.1109\/ICCV.2013.273"},{"issue":"1173","key":"55_CR14","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1098\/rspb.1980.0057","volume":"208","author":"HC Longuet-Higgins","year":"1980","unstructured":"Longuet-Higgins, H.C., Prazdny, K., et al.: The interpretation of a moving retinal image. Proc. R. Soc. Lond. B 208(1173), 385\u2013397 (1980)","journal-title":"Proc. R. Soc. Lond. B"},{"key":"55_CR15","unstructured":"Lucas, B.D., Kanade, T., et al.: An iterative image registration technique with an application to stereo vision (1981)"},{"key":"55_CR16","doi-asserted-by":"crossref","unstructured":"Mayer, N., et al.: A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4040\u20134048 (2016)","DOI":"10.1109\/CVPR.2016.438"},{"key":"55_CR17","doi-asserted-by":"crossref","unstructured":"Narayana, M., Hanson, A., Learned-Miller, E.: Coherent motion segmentation in moving camera videos using optical flow orientations, pp. 1577\u20131584 (2013)","DOI":"10.1109\/ICCV.2013.199"},{"issue":"6","key":"55_CR18","doi-asserted-by":"publisher","first-page":"1187","DOI":"10.1109\/TPAMI.2013.242","volume":"36","author":"P Ochs","year":"2014","unstructured":"Ochs, P., Malik, J., Brox, T.: Segmentation of moving objects by long term video analysis. IEEE Trans. Pattern Anal. Mach. Intell. 36(6), 1187\u20131200 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"55_CR19","doi-asserted-by":"crossref","unstructured":"Ogale, A.S., Ferm\u00fcller, C., Aloimonos, Y.: Motion segmentation using occlusions 27(6), 988\u2013992 (2005)","DOI":"10.1109\/TPAMI.2005.123"},{"key":"55_CR20","doi-asserted-by":"crossref","unstructured":"Perazzi, F., Pont-Tuset, J., McWilliams, B., Van Gool, L., Gross, M., Sorkine-Hornung, A.: A benchmark dataset and evaluation methodology for video object segmentation. In: Computer Vision and Pattern Recognition (2016)","DOI":"10.1109\/CVPR.2016.85"},{"key":"55_CR21","doi-asserted-by":"crossref","unstructured":"Prest, A., Leistner, C., Civera, J., Schmid, C., Ferrari, V.: Learning object class detectors from weakly annotated video. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3282\u20133289. IEEE (2012)","DOI":"10.1109\/CVPR.2012.6248065"},{"key":"55_CR22","doi-asserted-by":"crossref","unstructured":"Revaud, J., Weinzaepfel, P., Harchaoui, Z., Schmid, C.: EpicFlow: edge-preserving interpolation of correspondences for optical flow. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1164\u20131172 (2015)","DOI":"10.1109\/CVPR.2015.7298720"},{"issue":"3","key":"55_CR23","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., et al.: Imagenet large scale visual recognition challenge. Int. J. Comput. Vis. 115(3), 211\u2013252 (2015)","journal-title":"Int. J. Comput. Vis."},{"issue":"10","key":"55_CR24","doi-asserted-by":"publisher","first-page":"1191","DOI":"10.1109\/34.879803","volume":"22","author":"HS Sawhney","year":"2000","unstructured":"Sawhney, H.S., Guo, Y., Kumar, R.: Independent motion detection in 3d scenes. IEEE Trans. Pattern Anal. Mach. Intell. 22(10), 1191\u20131199 (2000)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"55_CR25","doi-asserted-by":"crossref","unstructured":"Sevilla-Lara, L., Sun, D., Jampani, V., Black, M.J.: Optical flow with semantic segmentation and localized layers. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3889\u20133898 (2016)","DOI":"10.1109\/CVPR.2016.422"},{"key":"55_CR26","doi-asserted-by":"crossref","unstructured":"Sun, D., Roth, S., Black, M.J.: Secrets of optical flow estimation and their principles. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2432\u20132439. IEEE (2010)","DOI":"10.1109\/CVPR.2010.5539939"},{"key":"55_CR27","doi-asserted-by":"crossref","unstructured":"Sun, D., Yang, X., Liu, M.Y., Kautz, J.: PWC-Net: CNNs for optical flow using pyramid, warping, and cost volume. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8934\u20138943 (2018)","DOI":"10.1109\/CVPR.2018.00931"},{"key":"55_CR28","doi-asserted-by":"crossref","unstructured":"Tang, K., Sukthankar, R., Yagnik, J., Fei-Fei, L.: Discriminative segment annotation in weakly labeled video. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 2483\u20132490 (2013)","DOI":"10.1109\/CVPR.2013.321"},{"key":"55_CR29","doi-asserted-by":"crossref","unstructured":"Tokmakov, P., Alahari, K., Schmid, C.: Learning motion patterns in videos. In: CVPR (2017)","DOI":"10.1109\/CVPR.2017.64"},{"key":"55_CR30","doi-asserted-by":"crossref","unstructured":"Tokmakov, P., Alahari, K., Schmid, C.: Learning video object segmentation with visual memory. In: ICCV (2017)","DOI":"10.1109\/ICCV.2017.480"},{"issue":"1740","key":"55_CR31","doi-asserted-by":"publisher","first-page":"1321","DOI":"10.1098\/rsta.1998.0224","volume":"356","author":"PH Torr","year":"1998","unstructured":"Torr, P.H.: Geometric motion segmentation and model selection. Philos. Trans. R. Soc. Lond. A: Math. Phys. Eng. Sci. 356(1740), 1321\u20131340 (1998)","journal-title":"Philos. Trans. R. Soc. Lond. A: Math. Phys. Eng. Sci."},{"key":"55_CR32","unstructured":"Vijayanarasimhan, S., Ricco, S., Schmid, C., Sukthankar, R., Fragkiadaki, K.: SfM-Net: learning of structure and motion from video. arXiv preprint arXiv:1704.07804 (2017)"},{"issue":"1\u20134","key":"55_CR33","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/0042-6989(62)90064-0","volume":"2","author":"G Walls","year":"1962","unstructured":"Walls, G.: The evolutionary history of eye movements. Vis. Res. 2(1\u20134), 69\u201380 (1962)","journal-title":"Vis. Res."},{"issue":"5","key":"55_CR34","doi-asserted-by":"publisher","first-page":"625","DOI":"10.1109\/83.334981","volume":"3","author":"JY Wang","year":"1994","unstructured":"Wang, J.Y., Adelson, E.H.: Representing moving images with layers. IEEE Trans. Image Process. 3(5), 625\u2013638 (1994)","journal-title":"IEEE Trans. Image Process."},{"key":"55_CR35","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1007\/978-3-642-33868-7_17","volume-title":"Computer Vision \u2013 ECCV 2012. Workshops and Demonstrations","author":"Jonas Wulff","year":"2012","unstructured":"Wulff, Jonas, Butler, Daniel J., Stanley, Garrett B., Black, Michael J.: Lessons and insights from creating a synthetic optical flow benchmark. In: Fusiello, Andrea, Murino, Vittorio, Cucchiara, Rita (eds.) ECCV 2012. LNCS, vol. 7584, pp. 168\u2013177. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33868-7_17"},{"key":"55_CR36","doi-asserted-by":"crossref","unstructured":"Wulff, J., Sevilla-Lara, L., Black, M.J.: Optical flow in mostly rigid scenes. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017","DOI":"10.1109\/CVPR.2017.731"},{"key":"55_CR37","doi-asserted-by":"crossref","unstructured":"Zamalieva, D., Yilmaz, A.: Background subtraction for the moving camera: a geometric approach 127, 73\u201385 (2014)","DOI":"10.1016\/j.cviu.2014.06.007"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2018 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-11024-6_55","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,22]],"date-time":"2023-01-22T01:09:32Z","timestamp":1674349772000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-11024-6_55"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030110239","9783030110246"],"references-count":37,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-11024-6_55","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"23 January 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Munich","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2018.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}