{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:06:22Z","timestamp":1760148382301,"version":"build-2065373602"},"reference-count":49,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,4,25]],"date-time":"2023-04-25T00:00:00Z","timestamp":1682380800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["U2003109","U21A20515","62102393","62206263","6227146","No. XDA23090304","Y201935","(SKLRS-2022-KF-11)","2022T150639","2021M703162"],"award-info":[{"award-number":["U2003109","U21A20515","62102393","62206263","6227146","No. XDA23090304","Y201935","(SKLRS-2022-KF-11)","2022T150639","2021M703162"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["U2003109","U21A20515","62102393","62206263","6227146","No. XDA23090304","Y201935","(SKLRS-2022-KF-11)","2022T150639","2021M703162"],"award-info":[{"award-number":["U2003109","U21A20515","62102393","62206263","6227146","No. XDA23090304","Y201935","(SKLRS-2022-KF-11)","2022T150639","2021M703162"]}]},{"DOI":"10.13039\/501100004739","name":"Youth Innovation Promotion Association","doi-asserted-by":"publisher","award":["U2003109","U21A20515","62102393","62206263","6227146","No. XDA23090304","Y201935","(SKLRS-2022-KF-11)","2022T150639","2021M703162"],"award-info":[{"award-number":["U2003109","U21A20515","62102393","62206263","6227146","No. XDA23090304","Y201935","(SKLRS-2022-KF-11)","2022T150639","2021M703162"]}],"id":[{"id":"10.13039\/501100004739","id-type":"DOI","asserted-by":"publisher"}]},{"name":"State Key Laboratory of Robotics and Systems (HIT)","award":["U2003109","U21A20515","62102393","62206263","6227146","No. XDA23090304","Y201935","(SKLRS-2022-KF-11)","2022T150639","2021M703162"],"award-info":[{"award-number":["U2003109","U21A20515","62102393","62206263","6227146","No. XDA23090304","Y201935","(SKLRS-2022-KF-11)","2022T150639","2021M703162"]}]},{"name":"Fundamental Research Funds for the Central Universities and China Postdoctoral Science Foundation","award":["U2003109","U21A20515","62102393","62206263","6227146","No. XDA23090304","Y201935","(SKLRS-2022-KF-11)","2022T150639","2021M703162"],"award-info":[{"award-number":["U2003109","U21A20515","62102393","62206263","6227146","No. XDA23090304","Y201935","(SKLRS-2022-KF-11)","2022T150639","2021M703162"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The surface mesh reconstruction from point clouds has been a fundamental research topic in Computer Vision and Computer Graphics. Recently, the Neural Implicit Representation (NIR)-based reconstruction has revolutionized this research topic. This work summarizes and analyzes representative works on NIR-based reconstruction and highlights several important insights. However, one major problem with existing works is that they struggle to handle high-resolution meshes. To address this, this paper introduces HRE-NDC, a novel High-Resolution and Efficient Neural Dual Contouring approach for mesh reconstruction from point clouds, which takes the previous state-of-the-art as a baseline and adopts a coarse-to-fine network structure design, along with feature-preserving downsampling and other improvements. HRE-NDC significantly reduces training time and memory usage while achieving better surface reconstruction results. Experimental results demonstrate the superiority of our method in both visualization and quantitative results, and it shows excellent generalization performance on various data including large indoor scenes, real-scanned urban buildings, clothing, and human bodies.<\/jats:p>","DOI":"10.3390\/rs15092267","type":"journal-article","created":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T01:16:25Z","timestamp":1682471785000},"page":"2267","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["High-Resolution and Efficient Neural Dual Contouring for Surface Reconstruction from Point Clouds"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4793-6039","authenticated-orcid":false,"given":"Qi","family":"Liu","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19 Yuquan Road, Shijingshan District, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1799-3948","authenticated-orcid":false,"given":"Jun","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19 Yuquan Road, Shijingshan District, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2517-7593","authenticated-orcid":false,"given":"Lupeng","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19 Yuquan Road, Shijingshan District, Beijing 100049, China"}]},{"given":"Yunbiao","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19 Yuquan Road, Shijingshan District, Beijing 100049, China"}]},{"given":"Ying","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19 Yuquan Road, Shijingshan District, Beijing 100049, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,25]]},"reference":[{"key":"ref_1","unstructured":"Berger, M., Tagliasacchi, A., Seversky, L.M., Alliez, P., Levine, J.a., Sharf, A., Silva, C.T., Tagliasacchi, A., Seversky, L.M., and Silva, C.T. 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