{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:15:32Z","timestamp":1767323732539,"version":"3.48.0"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819556984","type":"print"},{"value":"9789819556991","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-981-95-5699-1_34","type":"book-chapter","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:13:16Z","timestamp":1767323596000},"page":"493-506","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Geometry-Aware Diffusion for\u00a0Controllable Multi-view Aerial Generation"],"prefix":"10.1007","author":[{"given":"Na","family":"Yan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siyu","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaiji","family":"Hou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiulei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Tong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,2]]},"reference":[{"key":"34_CR1","doi-asserted-by":"crossref","unstructured":"Chu, Y., Tong, Q., Liu, X., Liu, X.: Odadapter: An effective method of semi-supervised object detection for aerial images. In: Chinese Conference on Pattern Recognition and Computer Vision (PRCV), pages 158\u2013172. Springer (2024)","DOI":"10.1007\/978-981-97-8502-5_12"},{"key":"34_CR2","doi-asserted-by":"crossref","unstructured":"Wu, R., et al.: Reconfusion: 3D reconstruction with diffusion priors. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pages 21551\u201321561 (2024)","DOI":"10.1109\/CVPR52733.2024.02036"},{"key":"34_CR3","unstructured":"Kingma, D.P., Welling, M.: Auto-encoding variational bayes. In: Proceedings of the 2nd International Conference on Learning Representations (ICLR), Banff, Canada (2014)"},{"key":"34_CR4","doi-asserted-by":"crossref","unstructured":"Park, E., Yang, J., Yumer, E., Ceylan, D., Berg, A.C.: Transformation-grounded image generation network for novel 3d view synthesis. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 3500\u20133509 (2017)","DOI":"10.1109\/CVPR.2017.82"},{"key":"34_CR5","unstructured":"Goodfellow, I.J., et al.: Generative adversarial nets. Adv. Neural Inf. Process. Syst. 27 (2014)"},{"key":"34_CR6","doi-asserted-by":"crossref","unstructured":"Tian, Y., Peng, X., Zhao, L., Zhang, S., Metaxas, D.N.: Crgan: learning complete representations for multi-view generation. arXiv preprint arXiv:1806.11191 (2018)","DOI":"10.24963\/ijcai.2018\/131"},{"key":"34_CR7","doi-asserted-by":"crossref","unstructured":"Xu, X., Chen, Y.-C., Jia, J.: View independent generative adversarial network for novel view synthesis. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pages. 7791\u20137800 (2019)","DOI":"10.1109\/ICCV.2019.00788"},{"key":"34_CR8","first-page":"6840","volume":"33","author":"J Ho","year":"2020","unstructured":"Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. Adv. Neural. Inf. Process. Syst. 33, 6840\u20136851 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"34_CR9","doi-asserted-by":"crossref","unstructured":"Chan, E.R., et al.:. Generative novel view synthesis with 3d-aware diffusion models. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pages 4217\u20134229 (2023)","DOI":"10.1109\/ICCV51070.2023.00389"},{"issue":"5","key":"34_CR10","first-page":"855","volume":"44","author":"XL Tang","year":"2018","unstructured":"Tang, X.L., Du, Y.M., Liu, Y.W., Li, J.X., Ma, Y.W.: Image recognition with conditional deep convolutional generative adversarial networks. Acta Automatica Sinica 44(5), 855\u2013864 (2018)","journal-title":"Acta Automatica Sinica"},{"key":"34_CR11","doi-asserted-by":"crossref","unstructured":"Zhu, J.-Y., Park, T., Isola, P., Efros, A.A.: Unpaired image-to-image translation using cycle-consistent adversarial networks. In: Proceedings of the IEEE International Conference on Computer Vision, pages 2223\u20132232 (2017)","DOI":"10.1109\/ICCV.2017.244"},{"key":"34_CR12","unstructured":"Song, J., Meng, C., Ermon, S.: Denoising diffusion implicit models. arXiv preprint arXiv:2010.02502 (2020)"},{"key":"34_CR13","doi-asserted-by":"crossref","unstructured":"Choy, C.B., Xu, D., Gwak, J., Chen, K., Savarese, S.: 3d-r2n2: A unified approach for single and multi-view 3d object reconstruction. In: Computer vision\u2013ECCV 2016: 14th European conference, Amsterdam, the Netherlands, October 11-14, 2016, proceedings, part VIII 14, pages 628\u2013644. Springer (2016)","DOI":"10.1007\/978-3-319-46484-8_38"},{"key":"34_CR14","doi-asserted-by":"crossref","unstructured":"Tang, H., Xu, D., Sebe, N., Wang, Y., Corso, J.J., Yan, Y.: Multi-channel attention selection GAN with cascaded semantic guidance for cross-view image translation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pages 2417\u20132426 (2019)","DOI":"10.1109\/CVPR.2019.00252"},{"key":"34_CR15","doi-asserted-by":"crossref","unstructured":"Zeng, Y., Lin, Z., Lu, H., Patel, V.M.: Cr-fill: Generative image inpainting with auxiliary contextual reconstruction. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pages 14164\u201314173 (2021)","DOI":"10.1109\/ICCV48922.2021.01390"},{"key":"34_CR16","doi-asserted-by":"crossref","unstructured":"Li, W., Lin, Z., Zhou, K., Qi, L., Wang, Y., Jia, J.: Mat: Mask-aware transformer for large hole image inpainting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pages 10758\u201310768 (2022)","DOI":"10.1109\/CVPR52688.2022.01049"},{"issue":"4","key":"34_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3592450","volume":"42","author":"O Avrahami","year":"2023","unstructured":"Avrahami, O., Fried, O., Lischinski, D.: Blended latent diffusion. ACM Trans. Graphics (TOG) 42(4), 1\u201311 (2023)","journal-title":"ACM Trans. Graphics (TOG)"},{"key":"34_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109897","volume":"145","author":"W Huang","year":"2024","unstructured":"Huang, W., Deng, Y., Hui, S., Yang, W., Zhou, S., Wang, J.: Sparse self-attention transformer for image inpainting. Pattern Recogn. 145, 109897 (2024)","journal-title":"Pattern Recogn."},{"issue":"3","key":"34_CR19","doi-asserted-by":"publisher","first-page":"1623","DOI":"10.1109\/TPAMI.2020.3019967","volume":"44","author":"R Ranftl","year":"2020","unstructured":"Ranftl, R., Lasinger, K., Hafner, D., Schindler, K., Koltun, V.: Towards robust monocular depth estimation: mixing datasets for zero-shot cross-dataset transfer. IEEE Trans. Pattern Anal. Mach. Intell. 44(3), 1623\u20131637 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"34_CR20","first-page":"25278","volume":"35","author":"C Schuhmann","year":"2022","unstructured":"Schuhmann, C., et al.: Laion-5b: An open large-scale dataset for training next generation image-text models. Adv. Neural. Inf. Process. Syst. 35, 25278\u201325294 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"34_CR21","doi-asserted-by":"crossref","unstructured":"Shih, M.-L., Su, S.-Y., Kopf, J., Huang, J.-B.: 3D photography using context-aware layered depth inpainting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pages. 8028\u20138038 (2020)","DOI":"10.1109\/CVPR42600.2020.00805"},{"key":"34_CR22","doi-asserted-by":"publisher","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: Convolutional Networks for Biomedical Image Segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28","DOI":"10.1007\/978-3-319-24574-4_28"},{"issue":"9","key":"34_CR23","doi-asserted-by":"publisher","first-page":"4825","DOI":"10.1109\/TCSVT.2023.3249204","volume":"33","author":"R Zhu","year":"2023","unstructured":"Zhu, R., Yin, L., Yang, M., Fei, W., Yang, Y., Wenbo, H.: Sues-200: A multi-height multi-scene cross-view image benchmark across drone and satellite. IEEE Trans. Circuits Syst. Video Technol. 33(9), 4825\u20134839 (2023)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"34_CR24","doi-asserted-by":"crossref","unstructured":"Zheng, Z., Wei, Y., Yang, Y.: University-1652: A multi-view multi-source benchmark for drone-based geo-localization. In: Proceedings of the 28th ACM International Conference on Multimedia, page.s 1395\u20131403 (2020)","DOI":"10.1145\/3394171.3413896"},{"key":"34_CR25","doi-asserted-by":"crossref","unstructured":"Schonberger, J.L., Frahm, J.-M.: Structure-from-motion revisited. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages. 4104\u20134113 (2016)","DOI":"10.1109\/CVPR.2016.445"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-5699-1_34","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:13:18Z","timestamp":1767323598000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5699-1_34"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819556984","9789819556991"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5699-1_34","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"2 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2025.prcv.cn\/index.asp","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}