{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T20:04:25Z","timestamp":1762027465663,"version":"build-2065373602"},"publisher-location":"New York, NY, USA","reference-count":36,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Natural Science Foundation ofChina (NSFC)","award":["No. 61722209","6181001011"],"award-info":[{"award-number":["No. 61722209","6181001011"]}]},{"name":"Shenzhen Science and Technology Research and Develop-ment Funds","award":["JCYJ20180507183706645","ZDYBH201900000002"],"award-info":[{"award-number":["JCYJ20180507183706645","ZDYBH201900000002"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,10,12]]},"DOI":"10.1145\/3394171.3413974","type":"proceedings-article","created":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T13:12:00Z","timestamp":1602508320000},"page":"3559-3567","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["All-in-depth via Cross-baseline Light Field Camera"],"prefix":"10.1145","author":[{"given":"Dingjian","family":"Jin","sequence":"first","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"given":"Anke","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"given":"Jiamin","family":"Wu","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"given":"Gaochang","family":"Wu","sequence":"additional","affiliation":[{"name":"Northeastern University, Shenyang, China"}]},{"given":"Haoqian","family":"Wang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"given":"Lu","family":"Fang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2020,10,12]]},"reference":[{"key":"e_1_3_2_2_1_1","unstructured":"[n.d.]. Blender software is used for 3d model construction. https:\/\/www.blender. org\/.  [n.d.]. Blender software is used for 3d model construction. https:\/\/www.blender. org\/."},{"volume-title":"Lytro redefines photography with light field cameras. .http:\/\/www.lytro. com\/","year":"2011","key":"e_1_3_2_2_2_1","unstructured":"[n.d.]. Lytro redefines photography with light field cameras. .http:\/\/www.lytro. com\/ . Press release, Jun 2011 . [n.d.]. Lytro redefines photography with light field cameras. .http:\/\/www.lytro. com\/. Press release,Jun 2011."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.452"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46487-9_38"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.168"},{"key":"e_1_3_2_2_6_1","volume-title":"The robust estimation of multiple motions: Parametric and piecewise-smooth flow fields. Computer vision and image understanding 63, 1","author":"Black Michael J","year":"1996","unstructured":"Michael J Black and Paul Anandan . 1996. The robust estimation of multiple motions: Parametric and piecewise-smooth flow fields. Computer vision and image understanding 63, 1 ( 1996 ), 75--104. Michael J Black and Paul Anandan. 1996. The robust estimation of multiple motions: Parametric and piecewise-smooth flow fields. Computer vision and image understanding 63, 1 (1996), 75--104."},{"key":"e_1_3_2_2_7_1","volume-title":"Large displacement optical flow: descriptor matching in variational motion estimation","author":"Brox Thomas","year":"2011","unstructured":"Thomas Brox and Jitendra Malik . 2011. Large displacement optical flow: descriptor matching in variational motion estimation . IEEE transactions on pattern analysis and machine intelligence 33, 3 ( 2011 ), 500--513. Thomas Brox and Jitendra Malik. 2011. Large displacement optical flow: descriptor matching in variational motion estimation. IEEE transactions on pattern analysis and machine intelligence 33, 3 (2011), 500--513."},{"key":"e_1_3_2_2_8_1","volume-title":"International journal of computer vision 61, 3","author":"Bruhn Andr\u00e9s","year":"2005","unstructured":"Andr\u00e9s Bruhn , Joachim Weickert , and Christoph Schn\u00f6rr . 2005. Lucas\/ Kanade meets Horn\/ Schunck : Combining local and global optic flow methods . International journal of computer vision 61, 3 ( 2005 ), 211--231. Andr\u00e9s Bruhn, Joachim Weickert, and Christoph Schn\u00f6rr. 2005. Lucas\/Kanade meets Horn\/Schunck: Combining local and global optic flow methods. International journal of computer vision 61, 3 (2005), 211--231."},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00567"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.197"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2839524"},{"key":"e_1_3_2_2_12_1","volume-title":"LiFF: Light Field Features in Scale and Depth. arXiv preprint arXiv:1901.03916 (Jan","author":"Dansereau Donald G.","year":"2019","unstructured":"Donald G. Dansereau , Bernd Girod , and Gordon Wetzstein . 2019. LiFF: Light Field Features in Scale and Depth. arXiv preprint arXiv:1901.03916 (Jan . 2019 ). https:\/\/arxiv.org\/abs\/1901.03916 Donald G. Dansereau, Bernd Girod, and Gordon Wetzstein. 2019. LiFF: Light Field Features in Scale and Depth. arXiv preprint arXiv:1901.03916 (Jan. 2019). https:\/\/arxiv.org\/abs\/1901.03916"},{"key":"e_1_3_2_2_13_1","volume-title":"Deep Ordinal Regression Network for Monocular Depth Estimation. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Fu Huan","year":"2018","unstructured":"Huan Fu , Mingming Gong , ChaohuiWang, Kayhan Batmanghelich , and Dacheng Tao . 2018 . Deep Ordinal Regression Network for Monocular Depth Estimation. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Huan Fu, Mingming Gong, ChaohuiWang, Kayhan Batmanghelich, and Dacheng Tao. 2018. Deep Ordinal Regression Network for Monocular Depth Estimation. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.5555\/2354409.2354978"},{"key":"e_1_3_2_2_15_1","volume-title":"Determining optical flow. Artificial intelligence 17, 1--3","author":"Horn Berthold KP","year":"1981","unstructured":"Berthold KP Horn and Brian G Schunck . 1981. Determining optical flow. Artificial intelligence 17, 1--3 ( 1981 ), 185--203. Berthold KP Horn and Brian G Schunck. 1981. Determining optical flow. Artificial intelligence 17, 1--3 (1981), 185--203."},{"key":"e_1_3_2_2_16_1","volume-title":"Bahram Javidi, and Yi-Pai Huang.","author":"Hsieh Po-Yuan","year":"2018","unstructured":"Po-Yuan Hsieh , Ping-Yen Chou , Hsiu-An Lin , Chao-Yu Chu , Cheng-Ting Huang , Chun-Ho Chen , Zong Qin , Manuel Martinez Corral , Bahram Javidi, and Yi-Pai Huang. 2018 . Long working range light field microscope with fast scanning multifocal liquid crystal microlens array. Optics express 26, 8 (2018), 10981-- 10996. Po-Yuan Hsieh, Ping-Yen Chou, Hsiu-An Lin, Chao-Yu Chu, Cheng-Ting Huang, Chun-Ho Chen, Zong Qin, Manuel Martinez Corral, Bahram Javidi, and Yi-Pai Huang. 2018. Long working range light field microscope with fast scanning multifocal liquid crystal microlens array. Optics express 26, 8 (2018), 10981-- 10996."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2014.6854871"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-14612-6_27"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2461912.2461926"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.242"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.614"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2014.358"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.226"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2017.108"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/IPTA.2016.7821011"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1117\/12.909882"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.207"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00931"},{"key":"e_1_3_2_2_29_1","volume-title":"Proceedings of the IEEE International Conference on Computer Vision. 673--680","author":"Hadap Sunil","year":"2013","unstructured":"MichaelWTao, Sunil Hadap , Jitendra Malik , and Ravi Ramamoorthi . 2013 . Depth from combining defocus and correspondence using light-field cameras . In Proceedings of the IEEE International Conference on Computer Vision. 673--680 . MichaelWTao, Sunil Hadap, Jitendra Malik, and Ravi Ramamoorthi. 2013. Depth from combining defocus and correspondence using light-field cameras. In Proceedings of the IEEE International Conference on Computer Vision. 673--680."},{"key":"e_1_3_2_2_30_1","volume-title":"Stereo DSO: Large-Scale Direct Sparse Visual Odometry With Stereo Cameras. In The IEEE International Conference on Computer Vision (ICCV).","author":"Wang Rui","year":"2017","unstructured":"Rui Wang , Martin Schworer , and Daniel Cremers . 2017 . Stereo DSO: Large-Scale Direct Sparse Visual Odometry With Stereo Cameras. In The IEEE International Conference on Computer Vision (ICCV). Rui Wang, Martin Schworer, and Daniel Cremers. 2017. Stereo DSO: Large-Scale Direct Sparse Visual Odometry With Stereo Cameras. In The IEEE International Conference on Computer Vision (ICCV)."},{"key":"e_1_3_2_2_31_1","volume-title":"Depth estimation with occlusion modeling using light-field cameras","author":"Efros Alexei A","year":"2016","unstructured":"Ting-ChunWang, Alexei A Efros , and Ravi Ramamoorthi . 2016. Depth estimation with occlusion modeling using light-field cameras . IEEE transactions on pattern analysis and machine intelligence 38, 11 ( 2016 ), 2170--2181. Ting-ChunWang, Alexei A Efros, and Ravi Ramamoorthi. 2016. Depth estimation with occlusion modeling using light-field cameras. IEEE transactions on pattern analysis and machine intelligence 38, 11 (2016), 2170--2181."},{"key":"e_1_3_2_2_32_1","article-title":"Light Field Video Capture Using a Learning-Based Hybrid Imaging System","volume":"36","author":"Wang Ting-Chun","year":"2017","unstructured":"Ting-Chun Wang , Jun-Yan Zhu , Nima Khademi Kalantari , Alexei A. Efros , and Ravi Ramamoorthi . 2017 . Light Field Video Capture Using a Learning-Based Hybrid Imaging System . ACM Transactions on Graphics (Proceedings of SIGGRAPH) 36 , 4 (2017). Ting-Chun Wang, Jun-Yan Zhu, Nima Khademi Kalantari, Alexei A. Efros, and Ravi Ramamoorthi. 2017. Light Field Video Capture Using a Learning-Based Hybrid Imaging System. ACM Transactions on Graphics (Proceedings of SIGGRAPH) 36, 4 (2017).","journal-title":"ACM Transactions on Graphics (Proceedings of SIGGRAPH)"},{"key":"e_1_3_2_2_33_1","volume-title":"2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 41--48","author":"Bastian Goldluecke SvenWanner","year":"2012","unstructured":"SvenWanner and Bastian Goldluecke . 2012 . Globally consistent depth labeling of 4D light fields . In 2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 41--48 . SvenWanner and Bastian Goldluecke. 2012. Globally consistent depth labeling of 4D light fields. In 2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 41--48."},{"key":"e_1_3_2_2_34_1","volume-title":"Proceedings of the IEEE International Conference on Computer Vision. 1385--1392","author":"Revaud Jerome","year":"2013","unstructured":"PhilippeWeinzaepfel, Jerome Revaud , Zaid Harchaoui , and Cordelia Schmid . 2013 . DeepFlow: Large displacement optical flow with deep matching . In Proceedings of the IEEE International Conference on Computer Vision. 1385--1392 . PhilippeWeinzaepfel, Jerome Revaud, Zaid Harchaoui, and Cordelia Schmid. 2013. DeepFlow: Large displacement optical flow with deep matching. In Proceedings of the IEEE International Conference on Computer Vision. 1385--1392."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.236"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.347"}],"event":{"name":"MM '20: The 28th ACM International Conference on Multimedia","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Seattle WA USA","acronym":"MM '20"},"container-title":["Proceedings of the 28th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3413974","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394171.3413974","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:32:07Z","timestamp":1750195927000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3413974"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,12]]},"references-count":36,"alternative-id":["10.1145\/3394171.3413974","10.1145\/3394171"],"URL":"https:\/\/doi.org\/10.1145\/3394171.3413974","relation":{},"subject":[],"published":{"date-parts":[[2020,10,12]]},"assertion":[{"value":"2020-10-12","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}