{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T06:18:36Z","timestamp":1778048316765,"version":"3.51.4"},"reference-count":97,"publisher":"IEEE","license":[{"start":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T00:00:00Z","timestamp":1772755200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T00:00:00Z","timestamp":1772755200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010450","name":"Nova","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010450","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,3,6]]},"DOI":"10.1109\/wacv61042.2026.00068","type":"proceedings-article","created":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T19:59:32Z","timestamp":1778011172000},"page":"623-634","source":"Crossref","is-referenced-by-count":0,"title":["Cluster-based Pseudo-labeling for Semi-Supervised LiDAR Semantic Segmentation"],"prefix":"10.1109","author":[{"given":"Qingju","family":"Guo","sequence":"first","affiliation":[{"name":"Beijing Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuang","family":"Li","sequence":"additional","affiliation":[{"name":"Beihang University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Geng","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Binhui","family":"Xie","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiawei","family":"Shan","sequence":"additional","affiliation":[{"name":"Tanway Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Li","sequence":"additional","affiliation":[{"name":"Nanjing University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.02071"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00967"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.52202\/075280-3482"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00939"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00330"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01164"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3390\/s21144813"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i2.27857"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2023.3241641"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.52202\/075280-3315"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00678"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00264"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i2.27887"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i2.16200"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00319"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-64559-5_16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA46639.2022.9811904"},{"key":"ref18","first-page":"226","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","volume-title":"KDD","author":"Ester"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.26599\/cvm.2025.9450514"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00761"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/358669.358692"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.5244\/C.34.154"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3076844"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3226029"},{"key":"ref25","first-page":"3809","article-title":"Revisiting point cloud shape classification with a simple and effective baseline","volume-title":"ICML","author":"Goyal"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19812-0_35"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19812-0_15"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2014.6906977"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3356612"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00636"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01687"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/3DV50981.2020.00052"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02079"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01298"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00314"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72646-0_15"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00903"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72667-5_13"},{"key":"ref39","first-page":"828","article-title":"Pointcnn: Convolution on x-transformed points","author":"Li","year":"2018","journal-title":"NeurIPS"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.00141"},{"key":"ref41","article-title":"Amvnet: Assertion-based multi-view fusion network for lidar semantic segmentation","author":"Liong","year":"2020"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.02550"},{"issue":"2","key":"ref43","first-page":"5","article-title":"Point discriminative learning for unsupervised representation learning on 3d point clouds","volume":"1","author":"Liu","year":"2021"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19842-7_5"},{"key":"ref45","article-title":"Box2seg: Learning semantics of 3d point clouds with box-level supervision","author":"Liu","year":"2022"},{"key":"ref46","article-title":"Segment any point cloud sequences by distilling vision foundation models","author":"Liu","year":"2023","journal-title":"NeurIPS"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-73232-4_5"},{"key":"ref48","article-title":"Learning from 2d: Contrastive pixel-to-point knowledge transfer for 3d pretraining","author":"Liu","year":"2021"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00177"},{"key":"ref50","article-title":"Decoupled weight decay regularization","volume-title":"ICLR","author":"Loshchilov"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093411"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2919741"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8967762"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/RAM.2013.6758588"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.00625"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3142440"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00505"},{"key":"ref58","first-page":"8024","article-title":"Pytorch: An imperative style, high-performance deep learning library","author":"Paszke","year":"2019","journal-title":"NeurIPS"},{"key":"ref59","article-title":"Sam-guided unsupervised domain adaptation for 3d segmentation","author":"Peng","year":"2023"},{"key":"ref60","first-page":"652","article-title":"Pointnet: Deep learning on point sets for 3d classification and segmentation","volume-title":"CVPR","author":"Qi"},{"key":"ref61","first-page":"5099","article-title":"Pointnet++: Deep hierarchical feature learning on point sets in a metric space","author":"Qi","year":"2017","journal-title":"NeurIPS"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00607"},{"key":"ref63","article-title":"GFNet: Geometric flow network for 3d point cloud semantic segmentation","author":"Qiu","year":"2022","journal-title":"Trans. on Mach. Learn. Res."},{"key":"ref64","first-page":"18559","article-title":"Benchmarking and analyzing point cloud classification under corruptions","volume-title":"ICML","author":"Ren"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48891.2023.10160539"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00966"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1007\/s41095-022-0281-9"},{"key":"ref68","article-title":"CALICO: Self-supervised camera-liDAR contrastive pre-training for BEV perception","volume-title":"ICLR","author":"Sun"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58604-1_41"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58604-1_41"},{"key":"ref71","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","author":"Tarvainen","year":"2017","journal-title":"NeurIPS"},{"key":"ref72","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","author":"Tarvainen","year":"2017","journal-title":"NeruIPS"},{"key":"ref73","article-title":"LiDAR: Sensing linear probing performance in joint embedding SSL architectures","volume-title":"ICLR","author":"Thilak"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00651"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00272"},{"key":"ref76","first-page":"7336","article-title":"Gool. 2d feature distillation for weakly-and semi-supervised 3d semantic segmentation","volume-title":"WACV","author":"Unal"},{"key":"ref77","article-title":"Club: Cluster meets BEV for liDAR-based 3d object detection","author":"Wang","year":"2023","journal-title":"NeurIPS"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01522"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00463"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1016\/j.cag.2023.09.006"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00508"},{"key":"ref82","first-page":"11035","article-title":"Polarmix: A general data augmentation technique for lidar point clouds","author":"Xiao","year":"2022","journal-title":"NeurIPS"},{"key":"ref83","article-title":"Annotator: An generic active learning baseline for lidar semantic segmentation","author":"Xie","year":"2023","journal-title":"NeurIPS"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01572"},{"key":"ref85","first-page":"989","article-title":"Cobevt: Cooperative bird\u2019s eye view semantic segmentation with sparse transformers","author":"Xu","year":"2022","journal-title":"CoRL"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01659"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19815-1_39"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-024-01991-2"},{"key":"ref89","article-title":"Mixsup: Mixed-grained supervision for label-efficient lidar-based 3d object detection","volume-title":"ICLR","author":"Yang"},{"key":"ref90","first-page":"17","article-title":"Proposal-contrast: Unsupervised pre-training for lidar-based 3d object detection","volume-title":"European conference on computer vision","author":"Yin"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00962"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01523"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01009"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02080"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636385"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00981"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01219-9_18"}],"event":{"name":"2026 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV)","location":"Tucson, AZ, USA","start":{"date-parts":[[2026,3,6]]},"end":{"date-parts":[[2026,3,10]]}},"container-title":["2026 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11491838\/11491925\/11492245.pdf?arnumber=11492245","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T05:55:34Z","timestamp":1778046934000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11492245\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,6]]},"references-count":97,"URL":"https:\/\/doi.org\/10.1109\/wacv61042.2026.00068","relation":{},"subject":[],"published":{"date-parts":[[2026,3,6]]}}}