{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T03:28:08Z","timestamp":1743132488408,"version":"3.40.3"},"publisher-location":"Cham","reference-count":46,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031730382"},{"type":"electronic","value":"9783031730399"}],"license":[{"start":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T00:00:00Z","timestamp":1730332800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T00:00:00Z","timestamp":1730332800000},"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\/978-3-031-73039-9_22","type":"book-chapter","created":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T14:57:07Z","timestamp":1730300227000},"page":"381-398","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Single-Photon 3D Imaging with\u00a0Equi-Depth Photon Histograms"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8895-5319","authenticated-orcid":false,"given":"Kaustubh","family":"Sadekar","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0002-9146-5411","authenticated-orcid":false,"given":"David","family":"Maier","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3695-5891","authenticated-orcid":false,"given":"Atul","family":"Ingle","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,10,31]]},"reference":[{"key":"22_CR1","unstructured":"Canon Inc.: Canon Launches MS-500 - The World\u2019s First Ultra-High-Sensitivity Interchangeable-Lens SPAD Sensor Camera. https:\/\/www.usa.canon.com\/newsroom\/2023\/20230801-ms500. Canon Press Release 8 January 2023. Accessed 25 Feb 2024"},{"issue":"4","key":"22_CR2","doi-asserted-by":"publisher","first-page":"834","DOI":"10.1109\/TPAMI.2017.2699184","volume":"40","author":"LC Chen","year":"2018","unstructured":"Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. IEEE Trans. Pattern Anal. Mach. Intell. 40(4), 834\u2013848 (2018). https:\/\/doi.org\/10.1109\/TPAMI.2017.2699184","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"22_CR3","unstructured":"Choi, S., Zhou, Q.Y., Koltun, V.: Robust reconstruction of indoor scenes. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015)"},{"key":"22_CR4","doi-asserted-by":"publisher","unstructured":"Colaco, A., Kirmani, A., Howland, G.A., Howell, J.C., Goyal, V.K.: Compressive depth map acquisition using a single photon-counting detector: Parametric signal processing meets sparsity. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, USA, 16\u201321 June 2012, pp. 96\u2013102. IEEE Computer Society (2012). https:\/\/doi.org\/10.1109\/CVPR.2012.6247663","DOI":"10.1109\/CVPR.2012.6247663"},{"key":"22_CR5","doi-asserted-by":"publisher","unstructured":"Curless, B., Levoy, M.: A volumetric method for building complex models from range images. In: Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 1996, pp. 303\u2013312. Association for Computing Machinery, New York, NY, USA (1996). https:\/\/doi.org\/10.1145\/237170.237269","DOI":"10.1145\/237170.237269"},{"key":"22_CR6","doi-asserted-by":"crossref","unstructured":"Deng, Z., Todorovic, S., Latecki, L.J.: Semantic segmentation of RGBD images with mutex constraints. In: Proceedings of the 2015 IEEE International Conference on Computer Vision (ICCV), ICCV 2015, pp. 1733\u20131741. IEEE Computer Society, USA (2015)","DOI":"10.1109\/ICCV.2015.202"},{"key":"22_CR7","doi-asserted-by":"crossref","unstructured":"Gupta, A., Ingle, A., Gupta, M.: Asynchronous single-photon 3D imaging. In: 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 7908\u20137917 (2019)","DOI":"10.1109\/ICCV.2019.00800"},{"key":"22_CR8","doi-asserted-by":"crossref","unstructured":"Gupta, A., Ingle, A., Velten, A., Gupta, M.: Photon-flooded single-photon 3D cameras. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2019","DOI":"10.1109\/CVPR.2019.00693"},{"key":"22_CR9","doi-asserted-by":"publisher","unstructured":"Gupta, S., Arbel\u00e1ez, P., Malik, J.: Perceptual organization and recognition of indoor scenes from RGB-D images. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp. 564\u2013571 (2013). https:\/\/doi.org\/10.1109\/CVPR.2013.79","DOI":"10.1109\/CVPR.2013.79"},{"key":"22_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1007\/978-3-319-10584-0_23","volume-title":"Computer Vision \u2013 ECCV 2014","author":"S 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: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8695, pp. 345\u2013360. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10584-0_23"},{"key":"22_CR11","doi-asserted-by":"publisher","unstructured":"Gutierrez-Barragan, F., Chen, H., Gupta, M., Velten, A., Gu, J.: iToF2dToF: a robust and flexible representation for data-driven time-of-flight imaging. IEEE Trans. Comput. Imaging 7, 1205\u20131214 (2021). https:\/\/doi.org\/10.1109\/TCI.2021.3126533","DOI":"10.1109\/TCI.2021.3126533"},{"key":"22_CR12","doi-asserted-by":"publisher","unstructured":"Gutierrez-Barragan, F., Ingle, A., Seets, T., Gupta, M., Velten, A.: Compressive single-photon 3D cameras. In: 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 17833\u201317843 (2022). https:\/\/doi.org\/10.1109\/CVPR52688.2022.01733","DOI":"10.1109\/CVPR52688.2022.01733"},{"issue":"6","key":"22_CR13","doi-asserted-by":"publisher","first-page":"2794","DOI":"10.1109\/TED.2021.3131430","volume":"69","author":"I Gyongy","year":"2022","unstructured":"Gyongy, I., Dutton, N.A.W., Henderson, R.K.: Direct time-of-flight single-photon imaging. IEEE Trans. Electron Devices 69(6), 2794\u20132805 (2022). https:\/\/doi.org\/10.1109\/TED.2021.3131430","journal-title":"IEEE Trans. Electron Devices"},{"key":"22_CR14","doi-asserted-by":"publisher","unstructured":"Hutchings, S.W., et al.: A reconfigurable 3-D-stacked SPAD imager with in-pixel histogramming for flash LIDAR or high-speed time-of-flight imaging. IEEE J. Solid-State Circuits 54(11), 2947\u20132956 (2019). https:\/\/doi.org\/10.1109\/JSSC.2019.2939083","DOI":"10.1109\/JSSC.2019.2939083"},{"key":"22_CR15","doi-asserted-by":"publisher","unstructured":"Ingle, A., Maier, D.: Count-free single-photon 3D imaging with race logic. IEEE Trans. Pattern Anal. Mach. Intell., 1\u201312 (2023). https:\/\/doi.org\/10.1109\/TPAMI.2023.3302822","DOI":"10.1109\/TPAMI.2023.3302822"},{"key":"22_CR16","unstructured":"Yoshida, J.: Breaking Down iPad Pro 11\u2019s LiDAR Scanner. https:\/\/www.eetimes.com\/breaking-down-ipad-pro-11s-lidar-scanner\/. EE Times 6\/5\/2020. Accessed 6 May 2021"},{"key":"22_CR17","unstructured":"Kim, B., Park, S., Han, S.H., Kim, S.J.: CMOS SPAD-based LiDAR sensors with zoom histogramming TDC architectures. ITE Tech. Rep. 46(41), 77\u201380 (2022)"},{"issue":"1","key":"22_CR18","doi-asserted-by":"publisher","first-page":"3158","DOI":"10.1038\/s41467-023-38893-9","volume":"14","author":"J Lee","year":"2023","unstructured":"Lee, J., Ingle, A., Chacko, J.V., Eliceiri, K.W., Gupta, M.: CASPI: collaborative photon processing for active single-photon imaging. Nat. Commun. 14(1), 3158 (2023)","journal-title":"Nat. Commun."},{"key":"22_CR19","doi-asserted-by":"crossref","unstructured":"Lin, Y., Charbon, E.: Spiking neural networks for active time-resolved SPAD imaging. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 8147\u20138156, January 2024","DOI":"10.1109\/WACV57701.2024.00796"},{"key":"22_CR20","doi-asserted-by":"publisher","unstructured":"Lindell, D.B., O\u2019Toole, M., Wetzstein, G.: Single-photon 3D imaging with deep sensor fusion. ACM Trans. Graph. 37(4) (2018). https:\/\/doi.org\/10.1145\/3197517.3201316","DOI":"10.1145\/3197517.3201316"},{"key":"22_CR21","doi-asserted-by":"crossref","unstructured":"Lindner, S., Zhang, C., Antolovic, I.M., Wolf, M., Charbon, E.: A 252 $$\\times $$ 144 SPAD pixel flash lidar with 1728 dual-clock 48.8 PS TDCs, integrated histogramming and 14.9-to-1 compression in 180NM CMOS technology. In: 2018 IEEE Symposium on VLSI Circuits, pp. 69\u201370 (2018)","DOI":"10.1109\/VLSIC.2018.8502386"},{"key":"22_CR22","doi-asserted-by":"publisher","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3431\u20133440 (2015). https:\/\/doi.org\/10.1109\/CVPR.2015.7298965","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"22_CR23","doi-asserted-by":"crossref","unstructured":"MacLean, J., Stewart, B., Gyongy, I.: TDC-less direct time-of-flight imaging using spiking neural networks (2024), arXiV preprint 2401.10793","DOI":"10.1109\/JSEN.2024.3454974"},{"key":"22_CR24","unstructured":"Ouster: Fully autonomous turbine inspection with Clobotics and Ouster (2022). https:\/\/ouster.com\/blog\/. Accessed 2 June 2022"},{"key":"22_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1007\/978-3-030-58539-6_14","volume-title":"Computer Vision \u2013 ECCV 2020","author":"J Peng","year":"2020","unstructured":"Peng, J., Xiong, Z., Huang, X., Li, Z.-P., Liu, D., Xu, F.: Photon-efficient 3D imaging with a non-local neural network. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12351, pp. 225\u2013241. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58539-6_14"},{"issue":"4","key":"22_CR26","first-page":"4180","volume":"45","author":"J Peng","year":"2022","unstructured":"Peng, J., Xiong, Z., Tan, H., Huang, X., Li, Z.P., Xu, F.: Boosting photon-efficient image reconstruction with a unified deep neural network. IEEE Trans. Pattern Anal. Mach. Intell. 45(4), 4180\u20134197 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"22_CR27","doi-asserted-by":"crossref","unstructured":"Po, R., Pediredla, A., Gkioulekas, I.: Adaptive gating for single-photon 3D imaging. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 16354\u201316363, June 2022","DOI":"10.1109\/CVPR52688.2022.01587"},{"key":"22_CR28","unstructured":"Rangwala, S.: The iPhone 12 - LiDAR at your fingertips (2022). https:\/\/www.forbes.com\/sites\/sabbirrangwala\/2020\/11\/12\/. Accessed 2 July 2022"},{"key":"22_CR29","doi-asserted-by":"publisher","unstructured":"Rapp, J., Ma, Y., Dawson, R.M.A., Goyal, V.K.: High-flux single-photon LiDAR. Optica 8(1), 30\u201339 (2021). https:\/\/doi.org\/10.1364\/OPTICA.403190","DOI":"10.1364\/OPTICA.403190"},{"key":"22_CR30","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"O Ronneberger","year":"2015","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"},{"issue":"4","key":"22_CR31","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1109\/MRA.2011.943233","volume":"18","author":"D Scaramuzza","year":"2011","unstructured":"Scaramuzza, D., Fraundorfer, F.: Visual odometry [tutorial]. IEEE Robot. Autom. Mag. 18(4), 80\u201392 (2011). https:\/\/doi.org\/10.1109\/MRA.2011.943233","journal-title":"IEEE Robot. Autom. Mag."},{"key":"22_CR32","doi-asserted-by":"publisher","unstructured":"Scharstein, D., Pal, C.: Learning conditional random fields for stereo. In: 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp.\u00a01\u20138 (2007). https:\/\/doi.org\/10.1109\/CVPR.2007.383191","DOI":"10.1109\/CVPR.2007.383191"},{"key":"22_CR33","doi-asserted-by":"publisher","unstructured":"Sheehan, M.P., Tachella, J., Davies, M.E.: A sketching framework for reduced data transfer in photon counting lidar. IEEE Trans. Comput. Imaging 7, 989\u20131004 (2021). https:\/\/doi.org\/10.1109\/TCI.2021.3113495","DOI":"10.1109\/TCI.2021.3113495"},{"issue":"1","key":"22_CR34","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/ncomms12046","volume":"7","author":"D Shin","year":"2016","unstructured":"Shin, D., et al.: Photon-efficient imaging with a single-photon camera. Nat. Commun. 7(1), 1\u20138 (2016). https:\/\/doi.org\/10.1038\/ncomms12046","journal-title":"Nat. Commun."},{"key":"22_CR35","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"746","DOI":"10.1007\/978-3-642-33715-4_54","volume-title":"Computer Vision \u2013 ECCV 2012","author":"N Silberman","year":"2012","unstructured":"Silberman, N., Hoiem, D., Kohli, P., Fergus, R.: Indoor segmentation and support inference from RGBD images. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7576, pp. 746\u2013760. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33715-4_54"},{"key":"22_CR36","doi-asserted-by":"publisher","unstructured":"Steinbr\u00fccker, F., Sturm, J., Cremers, D.: Real-time visual odometry from dense RGB-D images. IEEE Rob. Autom. Mag., 719\u2013722 (2011). https:\/\/doi.org\/10.1109\/ICCVW.2011.6130321","DOI":"10.1109\/ICCVW.2011.6130321"},{"key":"22_CR37","doi-asserted-by":"publisher","unstructured":"Sun, Z., Lindell, D.B., Solgaard, O., Wetzstein, G.: SPADnet: deep RGB-SPAD sensor fusion assisted by monocular depth estimation. Opt. Express 28(10), 14948\u201314962 (2020). https:\/\/doi.org\/10.1364\/OE.392386","DOI":"10.1364\/OE.392386"},{"key":"22_CR38","doi-asserted-by":"crossref","unstructured":"Tachella, J., Sheehan, M.P., Davies, M.E.: Sketched RT3D: how to reconstruct billions of photons per second. In: ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1566\u20131570 (2022)","DOI":"10.1109\/ICASSP43922.2022.9746304"},{"issue":"4","key":"22_CR39","doi-asserted-by":"publisher","first-page":"4656","DOI":"10.1109\/JSEN.2023.3342609","volume":"24","author":"A Tontini","year":"2024","unstructured":"Tontini, A., Mazzucchi, S., Passerone, R., Broseghini, N., Gasparini, L.: Histogram-Less LiDAR through SPAD response linearization. IEEE Sens. J. 24(4), 4656\u20134669 (2024). https:\/\/doi.org\/10.1109\/JSEN.2023.3342609","journal-title":"IEEE Sens. J."},{"issue":"9","key":"22_CR40","doi-asserted-by":"publisher","first-page":"3625","DOI":"10.1109\/TCSII.2022.3181687","volume":"69","author":"P Valentin","year":"2022","unstructured":"Valentin, P., William, G., David, C., Gilles, S.: A 2-stage EM algorithm for online peak detection, an application to TCSPC data. IEEE Trans. Circuits Syst. II Express Briefs 69(9), 3625\u20133629 (2022). https:\/\/doi.org\/10.1109\/TCSII.2022.3181687","journal-title":"IEEE Trans. Circuits Syst. II Express Briefs"},{"key":"22_CR41","doi-asserted-by":"crossref","unstructured":"Vornicu, I., Darie, A., Carmona-Galan, R., Rodriguez-Vazquez, A.: ToF estimation based on compressed real-time histogram builder for SPAD image sensors. In: 2019 IEEE International Symposium on Circuits and Systems (ISCAS), pp.\u00a01\u20134 (2019)","DOI":"10.1109\/ISCAS.2019.8702361"},{"key":"22_CR42","unstructured":"Wang, Y., Huang, W., Sun, F., Xu, T., Rong, Y., Huang, J.: Deep multimodal fusion by channel exchanging. In: Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M., Lin, H. (eds.) Advances in Neural Information Processing Systems, vol.\u00a033, pp. 4835\u20134845. Curran Associates, Inc. (2020)"},{"key":"22_CR43","unstructured":"Xie, E., Wang, W., Yu, Z., Anandkumar, A., Alvarez, J.M., Luo, P.: SegFormer: simple and efficient design for semantic segmentation with transformers. In: Neural Information Processing Systems (NeurIPS) (2021)"},{"key":"22_CR44","doi-asserted-by":"publisher","unstructured":"Zang, Z., Xiao, D., Li, D.D.U.: Non-fusion time-resolved depth image reconstruction using a highly efficient neural network architecture. Opt. Express 29(13), 19278\u201319291 (2021). https:\/\/doi.org\/10.1364\/OE.425917","DOI":"10.1364\/OE.425917"},{"key":"22_CR45","doi-asserted-by":"publisher","unstructured":"Zhao, H., Shi, J., Qi, X., Wang, X., Jia, J.: Pyramid scene parsing network. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6230\u20136239. IEEE Computer Society, Los Alamitos, CA, USA, July 2017. https:\/\/doi.org\/10.1109\/CVPR.2017.660","DOI":"10.1109\/CVPR.2017.660"},{"key":"22_CR46","unstructured":"Zhou, Q.Y., Park, J., Koltun, V.: Open3D: a modern library for 3D data processing. arXiv:1801.09847 (2018)"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-73039-9_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T15:26:53Z","timestamp":1730302013000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-73039-9_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,31]]},"ISBN":["9783031730382","9783031730399"],"references-count":46,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-73039-9_22","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,10,31]]},"assertion":[{"value":"31 October 2024","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":"Milan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","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":"29 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2024.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}