{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T19:25:59Z","timestamp":1776885959914,"version":"3.51.2"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819785070","type":"print"},{"value":"9789819785087","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,11,3]],"date-time":"2024-11-03T00:00:00Z","timestamp":1730592000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,3]],"date-time":"2024-11-03T00:00:00Z","timestamp":1730592000000},"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":[[2025]]},"DOI":"10.1007\/978-981-97-8508-7_3","type":"book-chapter","created":{"date-parts":[[2024,11,2]],"date-time":"2024-11-02T06:03:18Z","timestamp":1730527398000},"page":"32-45","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Multi-view Depth Estimation with\u00a0Adaptive Feature Extraction and\u00a0Region-Aware Depth Prediction"],"prefix":"10.1007","author":[{"given":"Chi","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingyu","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jijun","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,11,3]]},"reference":[{"key":"3_CR1","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1007\/s11263-016-0902-9","volume":"120","author":"H Aan\u00e6s","year":"2016","unstructured":"Aan\u00e6s, H., Jensen, R.R., Vogiatzis, G., Tola, E., Dahl, A.B.: Large-scale data for multiple-view stereopsis. Int. J. Comput. Vision 120, 153\u2013168 (2016)","journal-title":"Int. J. Comput. Vision"},{"key":"3_CR2","unstructured":"Cao, C., Ren, X., Fu, Y.: Mvsformer: multi-view stereo by learning robust image features and temperature-based depth. Trans. Mach. Learn. Res. (TMLR) (2023)"},{"key":"3_CR3","doi-asserted-by":"crossref","unstructured":"Collins, R.T.: A space-sweep approach to true multi-image matching. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 358\u2013363 (1996)","DOI":"10.1109\/CVPR.1996.517097"},{"key":"3_CR4","doi-asserted-by":"crossref","unstructured":"Darmon, F., Bascle, B., Devaux, J.C., Monasse, P., Aubry, M.: Deep multi-view stereo gone wild. In: 2021 International Conference on 3D Vision (3DV), pp. 484\u2013493 (2021)","DOI":"10.1109\/3DV53792.2021.00058"},{"key":"3_CR5","doi-asserted-by":"crossref","unstructured":"Ding, Y., Yuan, W., Zhu, Q., Zhang, H., Liu, X., Wang, Y., Liu, X.: Transmvsnet: global context-aware multi-view stereo network with transformers. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 8585\u20138594 (2022)","DOI":"10.1109\/CVPR52688.2022.00839"},{"key":"3_CR6","doi-asserted-by":"crossref","unstructured":"Galliani, S., Lasinger, K., Schindler, K.: Massively parallel multiview stereopsis by surface normal diffusion. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 873\u2013881 (2015)","DOI":"10.1109\/ICCV.2015.106"},{"key":"3_CR7","doi-asserted-by":"crossref","unstructured":"Gu, X., Fan, Z., Zhu, S., Dai, Z., Tan, F., Tan, P.: Cascade cost volume for high-resolution multi-view stereo and stereo matching. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2495\u20132504 (2020)","DOI":"10.1109\/CVPR42600.2020.00257"},{"key":"3_CR8","unstructured":"Katharopoulos, A., Vyas, A., Pappas, N., Fleuret, F.: Transformers are RNNS: fast autoregressive transformers with linear attention. In: International Conference on Machine Learning (ICML). pp. 5156\u20135165. PMLR (2020)"},{"key":"3_CR9","doi-asserted-by":"crossref","unstructured":"Li, B., Liu, Y., Wang, X.: Gradient harmonized single-stage detector. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol.\u00a033, pp. 8577\u20138584 (2019)","DOI":"10.1609\/aaai.v33i01.33018577"},{"key":"3_CR10","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Doll\u00e1r, P., Girshick, R., He, K., Hariharan, B., Belongie, S.: Feature pyramid networks for object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2117\u20132125 (2017)","DOI":"10.1109\/CVPR.2017.106"},{"key":"3_CR11","doi-asserted-by":"crossref","unstructured":"Ma, X., Gong, Y., Wang, Q., Huang, J., Chen, L., Yu, F.: Epp-mvsnet: Epipolar-assembling based depth prediction for multi-view stereo. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 5732\u20135740 (2021)","DOI":"10.1109\/ICCV48922.2021.00568"},{"key":"3_CR12","doi-asserted-by":"crossref","unstructured":"Peng, R., Wang, R., Wang, Z., Lai, Y., Wang, R.: Rethinking depth estimation for multi-view stereo: A unified representation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 8645\u20138654 (2022)","DOI":"10.1109\/CVPR52688.2022.00845"},{"key":"3_CR13","unstructured":"Zhu, Q., Min, C., Wei, Z., Chen, Y., Wang, G.: Deep learning for multi-view stereo via plane sweep: a survey (2021). arXiv:2106.15328"},{"key":"3_CR14","doi-asserted-by":"crossref","unstructured":"Sch\u00f6nberger, J.L., Zheng, E., Frahm, J.M., Pollefeys, M.: Pixelwise view selection for unstructured multi-view stereo. In: The European Conference on Computer Vision (ECCV), pp. 501\u2013518. Springer (2016)","DOI":"10.1007\/978-3-319-46487-9_31"},{"key":"3_CR15","doi-asserted-by":"crossref","unstructured":"Wang, X., Zhu, Z., Huang, G., Qin, F., Ye, Y., He, Y., Chi, X., Wang, X.: Mvster: epipolar transformer for efficient multi-view stereo. In: The European Conference on Computer Vision (ECCV), pp. 573\u2013591. Springer (2022)","DOI":"10.1007\/978-3-031-19821-2_33"},{"key":"3_CR16","doi-asserted-by":"crossref","unstructured":"Wei, Z., Zhu, Q., Min, C., Chen, Y., Wang, G.: Aa-rmvsnet: adaptive aggregation recurrent multi-view stereo network. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 6187\u20136196 (2021)","DOI":"10.1109\/ICCV48922.2021.00613"},{"issue":"8","key":"3_CR17","doi-asserted-by":"publisher","first-page":"10905","DOI":"10.1007\/s11063-023-11356-4","volume":"55","author":"S Xu","year":"2023","unstructured":"Xu, S., Xu, Q., Su, W., Tao, W.: Edge-aware spatial propagation network for multi-view depth estimation. Neural Process. Lett. 55(8), 10905\u201310923 (2023)","journal-title":"Neural Process. Lett."},{"key":"3_CR18","doi-asserted-by":"crossref","unstructured":"Yao, Y., Luo, Z., Li, S., Fang, T., Quan, L.: Mvsnet: depth inference for unstructured multi-view stereo. In: The European Conference on Computer Vision (ECCV), pp. 767\u2013783 (2018)","DOI":"10.1007\/978-3-030-01237-3_47"},{"key":"3_CR19","doi-asserted-by":"crossref","unstructured":"Yao, Y., Luo, Z., Li, S., Zhang, J., Ren, Y., Zhou, L., Fang, T., Quan, L.: Blendedmvs: a large-scale dataset for generalized multi-view stereo networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1790\u20131799 (2020)","DOI":"10.1109\/CVPR42600.2020.00186"},{"key":"3_CR20","unstructured":"Wei, Z., Zhu, Q., Min, C., Chen, Y., Wang, G.: Bidirectional hybrid LSTM based recurrent neural network for multi-view stereo. IEEE Trans. Visual. Comput. Graph. (TVCG) (2022)"},{"key":"3_CR21","unstructured":"Zhang, J., Yao, Y., Li, S., Luo, Z., Fang, T.: Visibility-aware multi-view stereo network. In: British Machine Vision Conference (BMVC) (2020)"},{"key":"3_CR22","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Peng, R., Hu, Y., Wang, R.: Geomvsnet: learning multi-view stereo with geometry perception. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 21508\u201321518 (2023)","DOI":"10.1109\/CVPR52729.2023.02060"},{"key":"3_CR23","doi-asserted-by":"crossref","unstructured":"Zhu, X., Hu, H., Lin, S., Dai, J.: Deformable convnets v2: more deformable, better results. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9308\u20139316 (2019)","DOI":"10.1109\/CVPR.2019.00953"},{"key":"3_CR24","doi-asserted-by":"crossref","unstructured":"Ren, H., Zhu, J., Chen, L., Jiang, X., Xie, K., Zhai, R.: Three-dimensional plant reconstruction with enhanced cascade-mvsnet. In: Chinese Conference on Pattern Recognition and Computer Vision (PRCV), pp. 283\u2013294. Springer (2023)","DOI":"10.1007\/978-981-99-8432-9_23"},{"key":"3_CR25","doi-asserted-by":"publisher","first-page":"448","DOI":"10.1016\/j.isprsjprs.2021.03.010","volume":"175","author":"A Yu","year":"2021","unstructured":"Yu, A., Guo, W., Liu, B., Chen, X., Wang, X., Cao, X., Jiang, B.: Attention aware cost volume pyramid based multi-view stereo network for 3d reconstruction. ISPRS J. Photogramm. Remote. Sens. 175, 448\u2013460 (2021)","journal-title":"ISPRS J. Photogramm. Remote. Sens."}],"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\/978-981-97-8508-7_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,2]],"date-time":"2024-11-02T06:12:30Z","timestamp":1730527950000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-8508-7_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,3]]},"ISBN":["9789819785070","9789819785087"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-8508-7_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,3]]},"assertion":[{"value":"3 November 2024","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":"Urumqi","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":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2024.prcv.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}