{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T19:12:16Z","timestamp":1775243536621,"version":"3.50.1"},"publisher-location":"Cham","reference-count":49,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030012694","type":"print"},{"value":"9783030012700","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-01270-0_26","type":"book-chapter","created":{"date-parts":[[2018,10,5]],"date-time":"2018-10-05T18:07:51Z","timestamp":1538762871000},"page":"438-454","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Reconstruction-Based Pairwise Depth Dataset for Depth Image Enhancement Using CNN"],"prefix":"10.1007","author":[{"given":"Junho","family":"Jeon","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seungyong","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,10,6]]},"reference":[{"key":"26_CR1","doi-asserted-by":"crossref","unstructured":"Agustsson, E., Timofte, R.: Ntire 2017 challenge on single image super-resolution: dataset and study. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 1122\u20131131 (2017)","DOI":"10.1109\/CVPRW.2017.150"},{"key":"26_CR2","unstructured":"Asus Xtion Pro Live: https:\/\/www.asus.com\/3D-Sensor\/Xtion_PRO_LIVE\/"},{"key":"26_CR3","doi-asserted-by":"crossref","unstructured":"Blum, M., Springenberg, J.T., W\u00fclfing, J., Riedmiller, M.: A learned feature descriptor for object recognition in RGB-D data. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA), pp. 1298\u20131303 (2012)","DOI":"10.1109\/ICRA.2012.6225188"},{"issue":"3","key":"26_CR4","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1023\/B:VISI.0000045324.43199.43","volume":"61","author":"A Bruhn","year":"2005","unstructured":"Bruhn, A., Weickert, J., Schn\u00f6rr, C.: Lucas\/Kanade meets Horn\/Schunck: combining local and global optic flow methods. Int. J. Comput. Vis. (IJCV) 61(3), 211\u2013231 (2005)","journal-title":"Int. J. Comput. Vis. (IJCV)"},{"key":"26_CR5","unstructured":"Chen, L., Lin, H., Li, S.: Depth image enhancement for Kinect using region growing and bilateral filter. In: Proceedings of International Conference on Pattern Recognition (ICPR), pp. 3070\u20133073 (2012)"},{"key":"26_CR6","doi-asserted-by":"crossref","unstructured":"Dai, A., Chang, A.X., Savva, M., Halber, M., Funkhouser, T., Nie\u00dfner, M.: Scannet: richly-annotated 3D reconstructions of indoor scenes. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2432\u20132443 (2017)","DOI":"10.1109\/CVPR.2017.261"},{"issue":"3","key":"26_CR7","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1145\/3054739","volume":"36","author":"A Dai","year":"2017","unstructured":"Dai, A., Nie\u00dfner, M., Zollh\u00f6fer, M., Izadi, S., Theobalt, C.: Bundlefusion: real-time globally consistent 3D reconstruction using on-the-fly surface reintegration. ACM Trans. Graph. (ToG) 36(3), 24 (2017)","journal-title":"ACM Trans. Graph. (ToG)"},{"key":"26_CR8","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: ImageNet: a large-scale hierarchical image database. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 248\u2013255 (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"26_CR9","unstructured":"Denton, E.L., Chintala, S., Fergus, R., et al.: Deep generative image models using a Laplacian pyramid of adversarial networks. In: Proceedings of Advances in Neural Information Processing Systems (NIPS), pp. 1486\u20131494 (2015)"},{"key":"26_CR10","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1007\/978-3-319-10593-2_13","volume-title":"Computer Vision \u2013 ECCV 2014","author":"Chao Dong","year":"2014","unstructured":"Dong, C., Loy, C.C., He, K., Tang, X.: Learning a deep convolutional network for image super-resolution. In: Proceedings of European Conference on Computer Vision (ECCV), pp. 184\u2013199 (2014)"},{"key":"26_CR11","doi-asserted-by":"crossref","unstructured":"Eitel, A., Springenberg, J.T., Spinello, L., Riedmiller, M., Burgard, W.: Multimodal deep learning for robust RGB-D object recognition. In: Proceedings of IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 681\u2013687 (2015)","DOI":"10.1109\/IROS.2015.7353446"},{"key":"26_CR12","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. In: Proceedings of Advances in Neural Information Processing Systems (NIPS), pp. 2672\u20132680 (2014)"},{"key":"26_CR13","doi-asserted-by":"crossref","unstructured":"Gu, S., Zuo, W., Guo, S., Chen, Y., Chen, C., Zhang, L.: Learning dynamic guidance for depth image enhancement. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 712\u2013721 (2017)","DOI":"10.1109\/CVPR.2017.83"},{"key":"26_CR14","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1007\/978-3-319-10584-0_23","volume-title":"Computer Vision \u2013 ECCV 2014","author":"Saurabh Gupta","year":"2014","unstructured":"Gupta, S., Girshick, R., Arbel\u00e1ez, P., Malik, J.: Learning rich features from RGB-D images for object detection and segmentation. In: Proceedings of European Conference on Computer Vision (ECCV), pp. 345\u2013360 (2014)"},{"key":"26_CR15","doi-asserted-by":"crossref","unstructured":"Han, Y., Lee, J.Y., Kweon, I.S.: High quality shape from a single RGB-D image under uncalibrated natural illumination. In: Proceedings of IEEE International Conference on Computer Vision (ICCV), pp. 1617\u20131624 (2013)","DOI":"10.1109\/ICCV.2013.204"},{"key":"26_CR16","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"26_CR17","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1007\/978-3-319-46487-9_22","volume-title":"Computer Vision \u2013 ECCV 2016","author":"Tak-Wai Hui","year":"2016","unstructured":"Hui, T.W., Loy, C.C., Tang, X.: Depth map super-resolution by deep multi-scale guidance. In: Proceedings of European Conference on Computer Vision (ECCV), pp. 353\u2013369 (2016)"},{"issue":"4","key":"26_CR18","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1145\/3072959.3073659","volume":"36","author":"S Iizuka","year":"2017","unstructured":"Iizuka, S., Simo-Serra, E., Ishikawa, H.: Globally and locally consistent image completion. ACM Trans. Graph. (ToG) 36(4), 107 (2017)","journal-title":"ACM Trans. Graph. (ToG)"},{"key":"26_CR19","doi-asserted-by":"crossref","unstructured":"Kiechle, M., Hawe, S., Kleinsteuber, M.: A joint intensity and depth co-sparse analysis model for depth map super-resolution. In: Proceedings of IEEE International Conference on Computer Vision (ICCV), pp. 1545\u20131552 (2013)","DOI":"10.1109\/ICCV.2013.195"},{"key":"26_CR20","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. In: Proceedings of International Conference on Learning Representations (ICLR) (2015)"},{"issue":"3","key":"26_CR21","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1145\/1276377.1276497","volume":"26","author":"J Kopf","year":"2007","unstructured":"Kopf, J., Cohen, M.F., Lischinski, D., Uyttendaele, M.: Joint bilateral upsampling. ACM Trans. Graphics (ToG) 26(3), 96 (2007)","journal-title":"ACM Trans. Graphics (ToG)"},{"key":"26_CR22","doi-asserted-by":"crossref","unstructured":"Kwon, H., Tai, Y.W., Lin, S.: Data-driven depth map refinement via multi-scale sparse representation. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 159\u2013167 (2015)","DOI":"10.1109\/CVPR.2015.7298611"},{"key":"26_CR23","doi-asserted-by":"crossref","unstructured":"Lai, W.S., Huang, J.B., Ahuja, N., Yang, M.H.: Deep Laplacian pyramid networks for fast and accurate super-resolution. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 624\u2013632 (2017)","DOI":"10.1109\/CVPR.2017.618"},{"issue":"7","key":"26_CR24","doi-asserted-by":"publisher","first-page":"11362","DOI":"10.3390\/s140711362","volume":"14","author":"AV Le","year":"2014","unstructured":"Le, A.V., Jung, S.W., Won, C.S.: Directional joint bilateral filter for depth images. Sensors 14(7), 11362\u201311378 (2014)","journal-title":"Sensors"},{"key":"26_CR25","doi-asserted-by":"crossref","unstructured":"Ledig, C., et al.: Photo-realistic single image super-resolution using a generative adversarial network. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4681\u20134690 (2017)","DOI":"10.1109\/CVPR.2017.19"},{"key":"26_CR26","doi-asserted-by":"crossref","unstructured":"Lin, D., Fidler, S., Urtasun, R.: Holistic scene understanding for 3D object detection with RGBD cameras. In: Proceedings of IEEE International Conference on Computer Vision (ICCV), pp. 1417\u20131424 (2013)","DOI":"10.1109\/ICCV.2013.179"},{"key":"26_CR27","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1007\/978-3-319-10602-1_48","volume-title":"Computer Vision \u2013 ECCV 2014","author":"Tsung-Yi Lin","year":"2014","unstructured":"Lin, T.Y., et al.: Microsoft COCO: common objects in context. In: Proceedings of European Conference on Computer Vision (ECCV), pp. 740\u2013755 (2014)"},{"key":"26_CR28","doi-asserted-by":"crossref","unstructured":"Lu, J., Forsyth, D.: Sparse depth super resolution. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2245\u20132253 (2015)","DOI":"10.1109\/CVPR.2015.7298837"},{"key":"26_CR29","doi-asserted-by":"crossref","unstructured":"Lu, S., Ren, X., Liu, F.: Depth enhancement via low-rank matrix completion. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3390\u20133397 (2014)","DOI":"10.1109\/CVPR.2014.433"},{"key":"26_CR30","doi-asserted-by":"crossref","unstructured":"Nah, S., Kim, T.H., Lee, K.M.: Deep multi-scale convolutional neural network for dynamic scene deblurring. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 257\u2013265 (2017)","DOI":"10.1109\/CVPR.2017.35"},{"key":"26_CR31","doi-asserted-by":"publisher","first-page":"746","DOI":"10.1007\/978-3-642-33715-4_54","volume-title":"Computer Vision \u2013 ECCV 2012","author":"Nathan Silberman","year":"2012","unstructured":"Silberman, N., Hoiem, D., Kohli, P., Fergus, R.: Indoor segmentation and support inference from RGBD images. In: Proceedings of European Conference on Computer Vision (ECCV), pp. 746\u2013760 (2012)"},{"key":"26_CR32","doi-asserted-by":"crossref","unstructured":"Newcombe, R.A., et al.: KinectFusion: real-time dense surface mapping and tracking. In: Proceedings of IEEE International Symposium on Mixed and Augmented Reality (ISMAR), pp. 127\u2013136 (2011)","DOI":"10.1109\/ISMAR.2011.6092378"},{"issue":"6","key":"26_CR33","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1145\/2508363.2508374","volume":"32","author":"M Nie\u00dfner","year":"2013","unstructured":"Nie\u00dfner, M., Zollh\u00f6fer, M., Izadi, S., Stamminger, M.: Real-time 3D reconstruction at scale using voxel hashing. ACM Trans. Graph. (ToG) 32(6), 169 (2013)","journal-title":"ACM Trans. Graph. (ToG)"},{"key":"26_CR34","unstructured":"Occipital Structure Sensor: https:\/\/structure.io\/"},{"key":"26_CR35","unstructured":"Paszke, A., Gross, S., Chintala, S., Chanan, G.: Pytorch: tensors and dynamic neural networks in python with strong GPU acceleration (2017)"},{"key":"26_CR36","doi-asserted-by":"crossref","unstructured":"Pathak, D., Kr\u00e4henb\u00fchl, P., Donahue, J., Darrell, T., Efros, A.: Context encoders: feature learning by inpainting. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2536\u20132544 (2016)","DOI":"10.1109\/CVPR.2016.278"},{"key":"26_CR37","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.patrec.2014.03.026","volume":"50","author":"Michael Schmeing","year":"2014","unstructured":"Schmeing, M., Jiang, X.: Edge-aware depth image filtering using color segmentation. Pattern Recognit. Lett. (PR) 50(C), 63\u201371 (2014)","journal-title":"Pattern Recognition Letters"},{"key":"26_CR38","doi-asserted-by":"crossref","unstructured":"Shen, X., Zhou, C., Xu, L., Jia, J.: Mutual-structure for joint filtering. In: Proceedings of IEEE International Conference on Computer Vision (ICCV), pp. 3406\u20133414 (2015)","DOI":"10.1109\/ICCV.2015.389"},{"key":"26_CR39","doi-asserted-by":"crossref","unstructured":"Song, S., Lichtenberg, S.P., Xiao, J.: Sun RGB-D: a RGB-D scene understanding benchmark suite. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 567\u2013576 (2015)","DOI":"10.1109\/CVPR.2015.7298655"},{"key":"26_CR40","doi-asserted-by":"crossref","unstructured":"Tomasi, C., Manduchi, R.: Bilateral filtering for gray and color images. In: Proceedings of IEEE International Conference on Computer Vision (ICCV), pp. 839\u2013846 (1998)","DOI":"10.1109\/ICCV.1998.710815"},{"issue":"5","key":"26_CR41","doi-asserted-by":"publisher","first-page":"2122","DOI":"10.1109\/TIP.2014.2312645","volume":"23","author":"I Tosic","year":"2014","unstructured":"Tosic, I., Drewes, S.: Learning joint intensity-depth sparse representations. IEEE Trans. Image Process. (TIP) 23(5), 2122\u20132132 (2014)","journal-title":"IEEE Trans. Image Process. (TIP)"},{"issue":"4","key":"26_CR42","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. (TIP) 13(4), 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process. (TIP)"},{"issue":"6","key":"26_CR43","first-page":"200","volume":"33","author":"C Wu","year":"2014","unstructured":"Wu, C., Zollh\u00f6fer, M., Nie\u00dfner, M., Stamminger, M., Izadi, S., Theobalt, C.: Real-time shading-based refinement for consumer depth cameras. ACM Trans. Graph. (ToG) 33(6), 200 (2014)","journal-title":"ACM Trans. Graph. (ToG)"},{"key":"26_CR44","unstructured":"Xu, L., Ren, J., Yan, Q., Liao, R., Jia, J.: Deep edge-aware filters. In: Proceedings of International Conference on Machine Learning (ICML), pp. 1669\u20131678 (2015)"},{"key":"26_CR45","unstructured":"Xu, L., Ren, J.S., Liu, C., Jia, J.: Deep convolutional neural network for image deconvolution. In: Proceedings of Advances in Neural Information Processing Systems (NIPS), pp. 1790\u20131798 (2014)"},{"key":"26_CR46","doi-asserted-by":"crossref","unstructured":"Yu, L.F., Yeung, S.K., Tai, Y.W., Lin, S.: Shading-based shape refinement of RGB-D images. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1415\u20131422 (2013)","DOI":"10.1109\/CVPR.2013.186"},{"key":"26_CR47","doi-asserted-by":"crossref","unstructured":"Zhang, L., Shen, P., Zhang, S., Song, J., Zhu, G.: Depth enhancement with improved exemplar-based inpainting and joint trilateral guided filtering. In: Proceedings of IEEE International Conference on Image Processing (ICIP), pp. 4102\u20134106 (2016)","DOI":"10.1109\/ICIP.2016.7533131"},{"key":"26_CR48","doi-asserted-by":"crossref","first-page":"815","DOI":"10.1007\/978-3-319-10578-9_53","volume-title":"Computer Vision \u2013 ECCV 2014","author":"Qi Zhang","year":"2014","unstructured":"Zhang, Q., Shen, X., Xu, L., Jia, J.: Rolling guidance filter. In: Proceedings of European Conference on Computer Vision (ECCV), pp. 815\u2013830 (2014)"},{"key":"26_CR49","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Funkhouser, T.: Deep depth completion of a single RGB-D image. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)","DOI":"10.1109\/CVPR.2018.00026"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-01270-0_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T18:39:17Z","timestamp":1775241557000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-01270-0_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030012694","9783030012700"],"references-count":49,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-01270-0_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"6 October 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Munich","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2018.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}