{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:27:50Z","timestamp":1750220870830,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":16,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,10,28]],"date-time":"2019-10-28T00:00:00Z","timestamp":1572220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,10,28]]},"DOI":"10.1145\/3359566.3360052","type":"proceedings-article","created":{"date-parts":[[2019,10,25]],"date-time":"2019-10-25T12:36:23Z","timestamp":1572006983000},"page":"1-6","source":"Crossref","is-referenced-by-count":2,"title":["Natural Posture Blending Using Deep Neural Networks"],"prefix":"10.1145","author":[{"given":"Felix","family":"Gaisbauer","sequence":"first","affiliation":[{"name":"Daimler AG, University of Ulm"}]},{"given":"Jannes","family":"Lehwald","sequence":"additional","affiliation":[{"name":"Daimler AG"}]},{"given":"Janis","family":"Sprenger","sequence":"additional","affiliation":[{"name":"German Research Center for Artificial Intelligence"}]},{"given":"Enrico","family":"Rukzio","sequence":"additional","affiliation":[{"name":"University of Ulm"}]}],"member":"320","published-online":{"date-parts":[[2019,10,28]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","DOI":"10.1109\/CA.1994.324011","volume-title":"Posture interpolation with collision avoidance","author":"Badler I","year":"1994"},{"key":"e_1_3_2_1_2_1","unstructured":"cmu. 2019. CMU Graphics Lab Motion Capture Database. http:\/\/mocap.cs.cmu.edu\/.  cmu. 2019. CMU Graphics Lab Motion Capture Database. http:\/\/mocap.cs.cmu.edu\/."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-34710-8_22"},{"volume-title":"EG 2018 - Posters, Eakta Jain and Jir\u00ed Kosinka (Eds.)","author":"Gaisbauer Felix","key":"e_1_3_2_1_4_1"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3072959.3073663"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"Daniel Holden Jun Saito Taku Komura and Thomas Joyce. 2015. Learning motion manifolds with convolutional autoencoders. In SIGGRAPH Asia 2015 Technical Briefs. ACM 18.  Daniel Holden Jun Saito Taku Komura and Thomas Joyce. 2015. Learning motion manifolds with convolutional autoencoders. In SIGGRAPH Asia 2015 Technical Briefs. ACM 18.","DOI":"10.1145\/2820903.2820918"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-16958-8_23"},{"volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980(2014). https:\/\/arxiv.org\/abs\/1412.6980","year":"2014","author":"Kingma P","key":"e_1_3_2_1_8_1"},{"key":"e_1_3_2_1_9_1","unstructured":"G\u00fcnter Klambauer Thomas Unterthiner Andreas Mayr and Sepp Hochreiter. 2017. Self-Normalizing Neural Networks. CoRR abs\/1706.02515(2017). arxiv:1706.02515  G\u00fcnter Klambauer Thomas Unterthiner Andreas Mayr and Sepp Hochreiter. 2017. Self-Normalizing Neural Networks. CoRR abs\/1706.02515(2017). arxiv:1706.02515"},{"key":"e_1_3_2_1_10_1","unstructured":"Yunpeng Li Dominik Roblek and Marco Tagliasacchi. 2019. From Here to There: Video Inbetweening Using Direct 3D Convolutions. arXiv preprint arXiv:1905.10240(2019).  Yunpeng Li Dominik Roblek and Marco Tagliasacchi. 2019. From Here to There: Video Inbetweening Using Direct 3D Convolutions. arXiv preprint arXiv:1905.10240(2019)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/41.538609"},{"volume-title":"An Energy-Driven Motion Planning Method for Two Distant Postures","year":"2014","author":"Wang He","key":"e_1_3_2_1_12_1"},{"key":"e_1_3_2_1_13_1","unstructured":"Yuichi Yagi. 2017. A filter based approach for inbetweening. ArXiv abs\/1706.03497(2017).  Yuichi Yagi. 2017. A filter based approach for inbetweening. ArXiv abs\/1706.03497(2017)."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3274247.3274502"},{"key":"e_1_3_2_1_15_1","unstructured":"Yi Zhou Connelly Barnes Jingwan Lu Jimei Yang and Hao Li. 2018a. On the Continuity of Rotation Representations in Neural Networks. arXiv preprint arXiv:1812.07035(2018).  Yi Zhou Connelly Barnes Jingwan Lu Jimei Yang and Hao Li. 2018a. On the Continuity of Rotation Representations in Neural Networks. arXiv preprint arXiv:1812.07035(2018)."},{"volume-title":"Auto-Conditioned Recurrent Networks for Extended Complex Human Motion Synthesis. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=r11Q2SlRW","year":"2018","author":"Zhou Yi","key":"e_1_3_2_1_16_1"}],"event":{"name":"MIG '19: Motion, Interaction and Games","sponsor":["SIGGRAPH ACM Special Interest Group on Computer Graphics and Interactive Techniques"],"location":"Newcastle upon Tyne United Kingdom","acronym":"MIG '19"},"container-title":["Motion, Interaction and Games"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3359566.3360052","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3359566.3360052","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:23:55Z","timestamp":1750202635000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3359566.3360052"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,28]]},"references-count":16,"alternative-id":["10.1145\/3359566.3360052","10.1145\/3359566"],"URL":"https:\/\/doi.org\/10.1145\/3359566.3360052","relation":{},"subject":[],"published":{"date-parts":[[2019,10,28]]}}}