{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T17:32:15Z","timestamp":1772040735454,"version":"3.50.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,8]]},"abstract":"<jats:p>Point Cloud Sampling and Recovery (PCSR) is critical for massive real-time point cloud collection and processing since raw data usually requires large storage and computation. This paper addresses a fundamental problem in PCSR: How to downsample the dense point cloud with arbitrary scales while preserving the local topology of discarded points in a case-agnostic manner (i.e., without additional storage for point relationships)? We propose a novel Locally Invertible Embedding (PointLIE) framework to unify the point cloud sampling and upsampling into one single framework through bi-directional learning. Specifically, PointLIE decouples the local geometric relationships between discarded points from the sampled points by progressively encoding the neighboring offsets to a latent variable. Once the latent variable is forced to obey a pre-defined distribution in the forward sampling path, the recovery can be achieved effectively through inverse operations. Taking the recover-pleasing sampled points and a latent embedding randomly drawn from the specified distribution as inputs, PointLIE can theoretically guarantee the fidelity of reconstruction and outperform state-of-the-arts quantitatively and qualitatively.<\/jats:p>","DOI":"10.24963\/ijcai.2021\/186","type":"proceedings-article","created":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:00:49Z","timestamp":1628679649000},"page":"1345-1351","source":"Crossref","is-referenced-by-count":8,"title":["PointLIE: Locally Invertible Embedding for Point Cloud Sampling and Recovery"],"prefix":"10.24963","author":[{"given":"Weibing","family":"Zhao","sequence":"first","affiliation":[{"name":"The Chinese University of Hong Kong, Shenzhen"},{"name":"Shenzhen Research Institute of Big Data"}]},{"given":"Xu","family":"Yan","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong, Shenzhen"},{"name":"Shenzhen Research Institute of Big Data"}]},{"given":"Jiantao","family":"Gao","sequence":"additional","affiliation":[{"name":"Shenzhen Research Institute of Big Data"},{"name":"Shanghai University"}]},{"given":"Ruimao","family":"Zhang","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong, Shenzhen"},{"name":"Shenzhen Research Institute of Big Data"}]},{"given":"Jiayan","family":"Zhang","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong, Shenzhen"}]},{"given":"Zhen","family":"Li","sequence":"additional","affiliation":[{"name":"Chinese University of Hong Kong, Shenzhen"},{"name":"Shenzhen Research Institute of Big Data"}]},{"given":"Song","family":"Wu","sequence":"additional","affiliation":[{"name":"Shenzhen Luohu Hospital"}]},{"given":"Shuguang","family":"Cui","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong, Shenzhen"},{"name":"Shenzhen Research Institute of Big Data"}]}],"member":"10584","event":{"name":"Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}","theme":"Artificial Intelligence","location":"Montreal, Canada","acronym":"IJCAI-2021","number":"30","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2021,8,19]]},"end":{"date-parts":[[2021,8,27]]}},"container-title":["Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:01:50Z","timestamp":1628679710000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2021\/186"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2021,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2021\/186","relation":{},"subject":[],"published":{"date-parts":[[2021,8]]}}}