{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T03:17:32Z","timestamp":1769915852039,"version":"3.49.0"},"reference-count":41,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,5,13]]},"DOI":"10.1109\/icra57147.2024.10611480","type":"proceedings-article","created":{"date-parts":[[2024,8,8]],"date-time":"2024-08-08T17:51:05Z","timestamp":1723139465000},"page":"14724-14731","source":"Crossref","is-referenced-by-count":22,"title":["LiDAR Data Synthesis with Denoising Diffusion Probabilistic Models"],"prefix":"10.1109","author":[{"given":"Kazuto","family":"Nakashima","sequence":"first","affiliation":[{"name":"Kyushu University,Faculty of Information Science and Electrical Engineering,Japan"}]},{"given":"Ryo","family":"Kurazume","sequence":"additional","affiliation":[{"name":"Kyushu University,Faculty of Information Science and Electrical Engineering,Japan"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3015992"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3116668"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8968535"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/iros51168.2021.9636747"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00131"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20050-2_2"},{"key":"ref7","article-title":"Auto-encoding variational bayes","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Kingma"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.5555\/2969033.2969125"},{"key":"ref9","first-page":"11895","article-title":"Generative modeling by estimating gradients of the data distribution","volume-title":"Proceedings of the Advances in neural information processing systems (NeurIPS)","author":"Song"},{"key":"ref10","first-page":"12438","article-title":"Improved techniques for training score-based generative models","volume-title":"Proceedings of the Advances in neural information processing systems (NeurIPS)","volume":"33","author":"Song"},{"key":"ref11","article-title":"Score-based generative modeling through stochastic differential equations","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Song"},{"key":"ref12","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume-title":"Proceedings of the Advances in Neural Information Processing Systems (NeurIPS)","volume":"33","author":"Ho"},{"key":"ref13","first-page":"8162","article-title":"Improved denoising diffusion probabilistic models","volume-title":"Proceedings of the International Conference on Machine Learning (ICML)","author":"Nichol"},{"key":"ref14","first-page":"21696","article-title":"Variational diffusion models","volume-title":"Proceedings of the Advances in neural information processing systems (NeurIPS)","volume":"34","author":"Kingma"},{"key":"ref15","first-page":"36479","article-title":"Photorealistic text-to-image diffusion models with deep language understanding","volume-title":"Proceedings of the Advances in Neural Information Processing Systems (NeurIPS)","volume":"35","author":"Saharia"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3179507"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913491297"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01117"},{"key":"ref19","first-page":"13213","article-title":"Simple diffusion: end-to-end diffusion for high resolution images","volume-title":"Proceedings of the International Conference on Machine Learning (ICML)","author":"Hoogeboom"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref21","article-title":"Monocular depth estimation using diffusion models","author":"Saxena","year":"2023"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01336"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01399"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00541"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2022.XVIII.005"},{"key":"ref26","first-page":"7537","article-title":"Fourier features let networks learn high frequency functions in low dimensional domains","volume-title":"Proceedings of the Advances in Neural Information Processing Systems (NeurIPS)","volume":"33","author":"Tancik"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_24"},{"key":"ref28","first-page":"8780","article-title":"Diffusion models beat gans on image synthesis","volume-title":"Proceedings of the Advances in neural information processing systems (NeurIPS)","volume":"34","author":"Dhariwal"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1080\/01691864.2018.1501279"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2019.8813862"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.549"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/IV47402.2020.9304631"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8967762"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00939"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/0047-259X(82)90077-X"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00396"},{"key":"ref37","first-page":"652","article-title":"PointNet: Deep learning on point sets for 3D classification and segmentation","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Qi"},{"key":"ref38","article-title":"ShapeNet: An information-rich 3D model repository","author":"Chang","year":"2015"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2020.103647"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA46639.2022.9811992"},{"key":"ref41","first-page":"1","article-title":"CARLA: An open urban driving simulator","volume-title":"Proceedings of the Conference on Robot Learning (CoRL)","author":"Dosovitskiy"}],"event":{"name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","location":"Yokohama, Japan","start":{"date-parts":[[2024,5,13]]},"end":{"date-parts":[[2024,5,17]]}},"container-title":["2024 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10609961\/10609862\/10611480.pdf?arnumber=10611480","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,11]],"date-time":"2024-08-11T04:18:15Z","timestamp":1723349895000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10611480\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":41,"URL":"https:\/\/doi.org\/10.1109\/icra57147.2024.10611480","relation":{},"subject":[],"published":{"date-parts":[[2024,5,13]]}}}