{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T02:33:58Z","timestamp":1789180438961,"version":"build-2803163510"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031723377","type":"print"},{"value":"9783031723384","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-72338-4_4","type":"book-chapter","created":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T10:03:01Z","timestamp":1726480981000},"page":"45-61","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Loci-Segmented: Improving Scene Segmentation Learning"],"prefix":"10.1007","author":[{"given":"Manuel","family":"Traub","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frederic","family":"Becker","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adrian","family":"Sauter","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebsastian","family":"Otte","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin V.","family":"Butz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,9,17]]},"reference":[{"key":"4_CR1","doi-asserted-by":"crossref","unstructured":"Bolya, D., Zhou, C., Xiao, F., Lee, Y.J.: Yolact: real-time instance segmentation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9157\u20139166 (2019)","DOI":"10.1109\/ICCV.2019.00925"},{"key":"4_CR2","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1111\/tops.12522","volume":"13","author":"MV Butz","year":"2021","unstructured":"Butz, M.V., Achimova, A., Bilkey, D., Knott, A.: Event-predictive cognition: a root for conceptual human thought. Top. Cogn. Sci. 13, 10\u201324 (2021). https:\/\/doi.org\/10.1111\/tops.12522","journal-title":"Top. Cogn. Sci."},{"key":"4_CR3","unstructured":"Dosovitskiy, A., et\u00a0al.: An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020)"},{"key":"4_CR4","unstructured":"Elsayed, G., Mahendran, A., van Steenkiste, S., Greff, K., Mozer, M.C., Kipf, T.: Savi++: towards end-to-end object-centric learning from real-world videos. In: Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K., Oh, A. (eds.) Advances in Neural Information Processing Systems, vol.\u00a035, pp. 28940\u201328954. Curran Associates, Inc"},{"key":"4_CR5","unstructured":"Greff, K., et\u00a0al.: Kubric: A scalable dataset generator. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3749\u20133761 (2022)"},{"key":"4_CR6","unstructured":"Greff, K., Van\u00a0Steenkiste, S., Schmidhuber, J.: On the binding problem in artificial neural networks. arXiv preprint arXiv:2012.05208 (2020)"},{"key":"4_CR7","unstructured":"Gumbsch, C., Butz, M.V., Martius, G.: Sparsely changing latent states for prediction and planning in partially observable domains. In: Ranzato, M., Beygelzimer, A., Dauphin, Y., Liang, P., Vaughan, J.W. (eds.) Advances in Neural Information Processing Systems, vol.\u00a034, pp. 17518\u201317531. Curran Associates, Inc. (2021), https:\/\/arxiv.org\/abs\/2110.15949"},{"key":"4_CR8","doi-asserted-by":"publisher","unstructured":"Ha, D., Schmidhuber, J.: World Models (2018). https:\/\/doi.org\/10.5281\/zenodo.1207631","DOI":"10.5281\/zenodo.1207631"},{"key":"4_CR9","doi-asserted-by":"publisher","unstructured":"Hafner, D., Lillicrap, T., Ba, J., Norouzi, M.: Dream to Control: Learning Behaviors by Latent Imagination (Mar 2020). https:\/\/doi.org\/10.48550\/arXiv.1912.01603","DOI":"10.48550\/arXiv.1912.01603"},{"key":"4_CR10","unstructured":"Hafner, D., Lillicrap, T., Fischer, I., Villegas, R., Ha, D., Lee, H., Davidson, J.: learning latent dynamics for planning from pixels. In: Proceedings of the 36th International Conference on Machine Learning, pp. 2555\u20132565. PMLR (May 2019), iSSN: 2640-3498"},{"key":"4_CR11","doi-asserted-by":"publisher","unstructured":"Heald, J.B., Lengyel, M., Wolpert, D.M.: Contextual inference in learning and memory. Trends Cognitive Sci. 27(1), 43\u201364 (2023). https:\/\/doi.org\/10.1016\/j.tics.2022.10.004, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1364661322002650","DOI":"10.1016\/j.tics.2022.10.004"},{"key":"4_CR12","doi-asserted-by":"crossref","unstructured":"Kalman, R.E.: A new approach to linear filtering and prediction problems. Trans. ASME\u2013J. Basic Eng. 82(Series D), 35\u201345 (1960)","DOI":"10.1115\/1.3662552"},{"key":"4_CR13","unstructured":"Kipf, T., et al.: Conditional object-centric learning from video. In: International Conference on Learning Representations (2022). https:\/\/openreview.net\/forum?id=aD7uesX1GF_"},{"key":"4_CR14","doi-asserted-by":"crossref","unstructured":"Liu, Z., Mao, H., Wu, C.Y., Feichtenhofer, C., Darrell, T., Xie, S.: A convnet for the 2020s. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11976\u201311986 (2022)","DOI":"10.1109\/CVPR52688.2022.01167"},{"key":"4_CR15","first-page":"11525","volume":"33","author":"F Locatello","year":"2020","unstructured":"Locatello, F., Weissenborn, D., Unterthiner, T., Mahendran, A., Heigold, G., Uszkoreit, J., Dosovitskiy, A., Kipf, T.: Object-centric learning with slot attention. Adv. Neural. Inf. Process. Syst. 33, 11525\u201311538 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"4_CR16","doi-asserted-by":"publisher","unstructured":"Mattar, M.G., Lengyel, M.: Planning in the brain. Neuron 110(6), 914\u2013934 (2022). https:\/\/doi.org\/10.1016\/j.neuron.2021.12.018, https:\/\/www.sciencedirect.com\/science\/article\/pii\/0896627321010357","DOI":"10.1016\/j.neuron.2021.12.018"},{"key":"4_CR17","unstructured":"Sabour, S., Frosst, N., Hinton, G.E.: Dynamic routing between capsules. Adv. Neural Inform. Process. Syst. 30 (2017)"},{"issue":"7839","key":"4_CR18","doi-asserted-by":"publisher","first-page":"604","DOI":"10.1038\/s41586-020-03051-4","volume":"588","author":"J Schrittwieser","year":"2020","unstructured":"Schrittwieser, J., et al.: Mastering atari, go, chess and shogi by planning with a learned model. Nature 588(7839), 604\u2013609 (2020). https:\/\/doi.org\/10.1038\/s41586-020-03051-4","journal-title":"Nature"},{"key":"4_CR19","doi-asserted-by":"publisher","unstructured":"Schw\u00f6bel, S., Markovi\u0107, D., Smolka, M.N., Kiebel, S.J.: Balancing control: A bayesian interpretation of habitual and goal-directed behavior. J. Math. Psychol. 100, 102472 (2021). https:\/\/doi.org\/10.1016\/j.jmp.2020.102472, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0022249620301000","DOI":"10.1016\/j.jmp.2020.102472"},{"key":"4_CR20","unstructured":"Traub, M., Becker, F., Otte, S., Butz, M.V.: Looping loci: Developing object permanence from videos. arXiv preprint arXiv:2310.10372 (2023)"},{"key":"4_CR21","unstructured":"Traub, M., Otte, S., Menge, T., Karlbauer, M., Thuemmel, J., Butz, M.V.: Learning what and where: Disentangling location and identity tracking without supervision. In: The Eleventh International Conference on Learning Representations (2023). https:\/\/openreview.net\/forum?id=NeDc-Ak-H_"},{"key":"4_CR22","unstructured":"Vaswani, A., et al.: Attention is all you need. Adv. Neural inform. Process. syst. 30 (2017)"},{"key":"4_CR23","unstructured":"Wu, Z., Dvornik, N., Greff, K., Kipf, T., Garg, A.: Slotformer: unsupervised visual dynamics simulation with object-centric models. In: The Eleventh International Conference on Learning Representations (2023). https:\/\/openreview.net\/forum?id=TFbwV6I0VLg"},{"key":"4_CR24","doi-asserted-by":"crossref","unstructured":"Yuan, J., Chen, T., Li, B., Xue, X.: Compositional scene representation learning via reconstruction: A survey (2023)","DOI":"10.1109\/TPAMI.2023.3286184"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72338-4_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T07:49:18Z","timestamp":1759996158000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72338-4_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031723377","9783031723384"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72338-4_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"17 September 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lugano","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Switzerland","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 September 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"33","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}