{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T14:47:58Z","timestamp":1779202078243,"version":"3.51.4"},"publisher-location":"Singapore","reference-count":34,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819749843","type":"print"},{"value":"9789819749850","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-97-4985-0_13","type":"book-chapter","created":{"date-parts":[[2024,7,15]],"date-time":"2024-07-15T11:07:08Z","timestamp":1721041628000},"page":"156-168","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Self-supervised Adversarial Masking for\u00a03D Point Cloud Representation Learning"],"prefix":"10.1007","author":[{"given":"Micha\u0142","family":"Szachniewicz","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wojciech","family":"Koz\u0142owski","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Micha\u0142","family":"Stypu\u0142kowski","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maciej","family":"Zi\u0119ba","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,7,16]]},"reference":[{"key":"13_CR1","doi-asserted-by":"crossref","unstructured":"Afham, M., Dissanayake, I., Dissanayake, D., Dharmasiri, A., Thilakarathna, K., Rodrigo, R.: Crosspoint: self-supervised cross-modal contrastive learning for 3D point cloud understanding (2022)","DOI":"10.1109\/CVPR52688.2022.00967"},{"key":"13_CR2","unstructured":"Baevski, A., Hsu, W.N., Xu, Q., Babu, A., Gu, J., Auli, M.: data2vec: A general framework for self-supervised learning in speech, vision and language (2022)"},{"key":"13_CR3","doi-asserted-by":"crossref","unstructured":"Caron, M., et al.: Emerging properties in self-supervised vision transformers (2021)","DOI":"10.1109\/ICCV48922.2021.00951"},{"key":"13_CR4","unstructured":"Chang, A.X., et al.: Shapenet: an information-rich 3D model repository (2015)"},{"key":"13_CR5","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding (2019)"},{"key":"13_CR6","doi-asserted-by":"crossref","unstructured":"Han, Z., Shang, M., Liu, Y.S., Zwicker, M.: View inter-prediction GAN: unsupervised representation learning for 3D shapes by learning global shape memories to support local view predictions (2018)","DOI":"10.1609\/aaai.v33i01.33018376"},{"key":"13_CR7","doi-asserted-by":"crossref","unstructured":"Han, Z., Wang, X., Liu, Y.S., Zwicker, M.: Multi-angle point cloud-VAE: unsupervised feature learning for 3D point clouds from multiple angles by joint self-reconstruction and half-to-half prediction (2019)","DOI":"10.1109\/ICCV.2019.01054"},{"key":"13_CR8","doi-asserted-by":"crossref","unstructured":"He, K., Chen, X., Xie, S., Li, Y., Doll\u00e1r, P., Girshick, R.: Masked autoencoders are scalable vision learners. In: CVPR, pp. 16000\u201316009 (2022)","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"13_CR9","unstructured":"Hendrycks, D., Gimpel, K.: Gaussian error linear units (gelus) (2020)"},{"key":"13_CR10","doi-asserted-by":"crossref","unstructured":"Li, J., Chen, B.M., Lee, G.H.: So-net: Self-organizing network for point cloud analysis (2018)","DOI":"10.1109\/CVPR.2018.00979"},{"key":"13_CR11","unstructured":"Li, Y., Bu, R., Sun, M., Wu, W., Di, X., Chen, B.: PointCNN: convolution on x-transformed points. In: NeurIPS, vol.\u00a031. Curran Associates, Inc. (2018)"},{"key":"13_CR12","doi-asserted-by":"crossref","unstructured":"Liu, H., Cai, M., Lee, Y.J.: Masked discrimination for self-supervised learning on point clouds (2022)","DOI":"10.1007\/978-3-031-20086-1_38"},{"key":"13_CR13","doi-asserted-by":"crossref","unstructured":"Pang, Y., Wang, W., Tay, F.E.H., Liu, W., Tian, Y., Yuan, L.: Masked autoencoders for point cloud self-supervised learning (2022)","DOI":"10.1007\/978-3-031-20086-1_35"},{"key":"13_CR14","unstructured":"Qi, C.R., Su, H., Mo, K., Guibas, L.J.: Pointnet: deep learning on point sets for 3D classification and segmentation (2017)"},{"key":"13_CR15","unstructured":"Qi, C.R., Yi, L., Su, H., Guibas, L.J.: Pointnet++: deep hierarchical feature learning on point sets in a metric space (2017)"},{"key":"13_CR16","unstructured":"Sauder, J., Sievers, B.: Self-supervised deep learning on point clouds by reconstructing space (2019)"},{"key":"13_CR17","unstructured":"Shazeer, N.: GLU variants improve transformer (2020)"},{"key":"13_CR18","unstructured":"Shi, Y., Siddharth, N., Torr, P.H.S., Kosiorek, A.R.: Adversarial masking for self-supervised learning (2022)"},{"key":"13_CR19","doi-asserted-by":"crossref","unstructured":"Uy, M.A., Pham, Q.H., Hua, B.S., Nguyen, D.T., Yeung, S.K.: Revisiting point cloud classification: a new benchmark dataset and classification model on real-world data (2019)","DOI":"10.1109\/ICCV.2019.00167"},{"key":"13_CR20","unstructured":"Valsesia, D., Fracastoro, G., Magli, E.: Learning localized generative models for 3D point clouds via graph convolution. In: ICLR (2019)"},{"key":"13_CR21","doi-asserted-by":"crossref","unstructured":"Wang, H., Liu, Q., Yue, X., Lasenby, J., Kusner, M.J.: Unsupervised point cloud pre-training via occlusion completion (2021)","DOI":"10.1109\/ICCV48922.2021.00964"},{"key":"13_CR22","doi-asserted-by":"crossref","unstructured":"Wang, Y., Sun, Y., Liu, Z., Sarma, S.E., Bronstein, M.M., Solomon, J.M.: Dynamic graph CNN for learning on point clouds (2019)","DOI":"10.1145\/3326362"},{"key":"13_CR23","unstructured":"Wu, J., Zhang, C., Xue, T., Freeman, W.T., Tenenbaum, J.B.: Learning a probabilistic latent space of object shapes via 3D generative-adversarial modeling (2017)"},{"key":"13_CR24","unstructured":"Wu, Z., et al.: 3D shapenets: a deep representation for volumetric shapes (2015)"},{"key":"13_CR25","doi-asserted-by":"crossref","unstructured":"Xie, S., Gu, J., Guo, D., Qi, C.R., Guibas, L.J., Litany, O.: Pointcontrast: unsupervised pre-training for 3D point cloud understanding (2020)","DOI":"10.1007\/978-3-030-58580-8_34"},{"key":"13_CR26","doi-asserted-by":"crossref","unstructured":"Yan, S., et al.: Implicit autoencoder for point cloud self-supervised representation learning (2023)","DOI":"10.1109\/ICCV51070.2023.01336"},{"key":"13_CR27","doi-asserted-by":"crossref","unstructured":"Yang, Y., Feng, C., Shen, Y., Tian, D.: Foldingnet: point cloud auto-encoder via deep grid deformation (2018)","DOI":"10.1109\/CVPR.2018.00029"},{"key":"13_CR28","doi-asserted-by":"crossref","unstructured":"Yu, X., Tang, L., Rao, Y., Huang, T., Zhou, J., Lu, J.: Point-BERT: pre-training 3D point cloud transformers with masked point modeling (2022)","DOI":"10.1109\/CVPR52688.2022.01871"},{"key":"13_CR29","unstructured":"Zhang, R., et al.: Point-m2ae: multi-scale masked autoencoders for hierarchical point cloud pre-training (2022)"},{"key":"13_CR30","unstructured":"Zhang, T., Li, W.: kdecay: Just adding k-decay items on learning-rate schedule to improve neural networks (2022)"},{"key":"13_CR31","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Girdhar, R., Joulin, A., Misra, I.: Self-supervised pretraining of 3D features on any point-cloud (2021)","DOI":"10.1109\/ICCV48922.2021.01009"},{"key":"13_CR32","unstructured":"Zheng, H., Fu, J., Zha, Z.J., Luo, J.: Learning deep bilinear transformation for fine-grained image representation (2019)"},{"key":"13_CR33","unstructured":"Zhou, J., et al.: iBot: image BERT pre-training with online tokenizer (2022)"},{"key":"13_CR34","unstructured":"Zhou, J., et al.: 3D-OAE: occlusion auto-encoders for self-supervised learning on point clouds (2022)"}],"container-title":["Lecture Notes in Computer Science","Intelligent Information and Database Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-4985-0_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,15]],"date-time":"2024-07-15T11:13:12Z","timestamp":1721041992000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-4985-0_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819749843","9789819749850"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-4985-0_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"16 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ACIIDS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asian Conference on Intelligent Information and Database Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ras Al Khaimah","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Arab Emirates","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 April 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 April 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aciids2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aciids.pwr.edu.pl\/2024\/index.php#about","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}