{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T01:42:41Z","timestamp":1784943761430,"version":"3.55.0"},"publisher-location":"Cham","reference-count":46,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030012335","type":"print"},{"value":"9783030012342","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\/978-3-030-01234-2_22","type":"book-chapter","created":{"date-parts":[[2018,10,5]],"date-time":"2018-10-05T16:13:11Z","timestamp":1538755991000},"page":"363-380","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":246,"title":["Superpixel Sampling Networks"],"prefix":"10.1007","author":[{"given":"Varun","family":"Jampani","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deqing","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming-Yu","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming-Hsuan","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan","family":"Kautz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2018,10,6]]},"reference":[{"issue":"11","key":"22_CR1","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","volume":"34","author":"R Achanta","year":"2012","unstructured":"Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., S\u00fcsstrunk, S.: SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 34(11), 2274\u20132282 (2012)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI)"},{"key":"22_CR2","doi-asserted-by":"crossref","unstructured":"Achanta, R., Susstrunk, S.: Superpixels and polygons using simple non-iterative clustering. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017)","DOI":"10.1109\/CVPR.2017.520"},{"key":"22_CR3","unstructured":"Aljalbout, E., Golkov, V., Siddiqui, Y., Cremers, D.: Clustering with deep learning: taxonomy and new methods. arXiv preprint arXiv:1801.07648 (2018)"},{"issue":"5","key":"22_CR4","doi-asserted-by":"publisher","first-page":"898","DOI":"10.1109\/TPAMI.2010.161","volume":"33","author":"P Arbelaez","year":"2011","unstructured":"Arbelaez, P., Maire, M., Fowlkes, C., Malik, J.: Contour detection and hierarchical image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 33(5), 898\u2013916 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI)"},{"issue":"3","key":"22_CR5","doi-asserted-by":"publisher","first-page":"298","DOI":"10.1007\/s11263-014-0744-2","volume":"111","author":"M Van den Bergh","year":"2015","unstructured":"Van den Bergh, M., Boix, X., Roig, G., Van Gool, L.: SEEDS: superpixels extracted via energy-driven sampling. Int. J. Comput. Vis. (IJCV) 111(3), 298\u2013314 (2015)","journal-title":"Int. J. Comput. Vis. (IJCV)"},{"key":"22_CR6","doi-asserted-by":"crossref","unstructured":"Van den Bergh, M., Carton, D., Van Gool, L.: Depth SEEDS: recovering incomplete depth data using superpixels. In: IEEE Workshop on Applications of Computer Vision (WACV), pp. 363\u2013368 (2013)","DOI":"10.1109\/WACV.2013.6475041"},{"key":"22_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1007\/978-3-642-33783-3_44","volume-title":"Computer Vision \u2013 ECCV 2012","author":"DJ Butler","year":"2012","unstructured":"Butler, D.J., Wulff, J., Stanley, G.B., Black, M.J.: A naturalistic open source movie for optical flow evaluation. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7577, pp. 611\u2013625. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33783-3_44"},{"key":"22_CR8","unstructured":"Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: Semantic image segmentation with deep convolutional nets and fully connected CRFs. In: International Conference on Learning Representations (ICLR) (2015)"},{"issue":"5","key":"22_CR9","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1109\/34.1000236","volume":"24","author":"D Comaniciu","year":"2002","unstructured":"Comaniciu, D., Meer, P.: Mean shift: a robust approach toward feature space analysis. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 24(5), 603\u2013619 (2002)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI)"},{"key":"22_CR10","doi-asserted-by":"crossref","unstructured":"Cordts, M., et al.: The cityscapes dataset for semantic urban scene understanding. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)","DOI":"10.1109\/CVPR.2016.350"},{"issue":"1","key":"22_CR11","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1007\/s11263-014-0733-5","volume":"111","author":"M Everingham","year":"2015","unstructured":"Everingham, M., Eslami, S.A., Van Gool, L., Williams, C.K., Winn, J., Zisserman, A.: The Pascal visual object classes challenge: a retrospective. Int. J. Comput. Vis. (IJCV) 111(1), 98\u2013136 (2015)","journal-title":"Int. J. Comput. Vis. (IJCV)"},{"key":"22_CR12","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1023\/B:VISI.0000022288.19776.77","volume":"59","author":"PF Felzenszwalb","year":"2004","unstructured":"Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient graph-based image segmentation. International J. Comput. Vis. (IJCV) 59, 167\u2013181 (2004)","journal-title":"International J. Comput. Vis. (IJCV)"},{"key":"22_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"597","DOI":"10.1007\/978-3-319-46448-0_36","volume-title":"Computer Vision \u2013 ECCV 2016","author":"R Gadde","year":"2016","unstructured":"Gadde, R., Jampani, V., Kiefel, M., Kappler, D., Gehler, P.V.: Superpixel convolutional networks using bilateral inceptions. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 597\u2013613. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_36"},{"key":"22_CR14","doi-asserted-by":"crossref","unstructured":"Giraud, R., Ta, V.T., Papadakis, N.: SCALP: superpixels with contour adherence using linear path. In: International Conference on Pattern Recognition (ICPR) (2016)","DOI":"10.1109\/ICPR.2016.7899991"},{"issue":"3","key":"22_CR15","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1007\/s11263-008-0140-x","volume":"80","author":"S Gould","year":"2008","unstructured":"Gould, S., Rodgers, J., Cohen, D., Elidan, G., Koller, D.: Multi-class segmentation with relative location prior. Int. J. Comput. Vis. 80(3), 300\u2013316 (2008)","journal-title":"Int. J. Comput. Vis."},{"key":"22_CR16","unstructured":"Greff, K., Rasmus, A., Berglund, M., Hao, T., Valpola, H., Schmidhuber, J.: Tagger: deep unsupervised perceptual grouping. In: Advances in Neural Information Processing Systems (NIPS) (2016)"},{"key":"22_CR17","unstructured":"Greff, K., van Steenkiste, S., Schmidhuber, J.: Neural expectation maximization. In: Advances in Neural Information Processing Systems (NIPS) (2017)"},{"issue":"3","key":"22_CR18","doi-asserted-by":"publisher","first-page":"330","DOI":"10.1007\/s11263-015-0822-0","volume":"115","author":"S He","year":"2015","unstructured":"He, S., Lau, R.W., Liu, W., Huang, Z., Yang, Q.: SuperCNN: a superpixelwise convolutional neural network for salient object detection. Int. J. Comput. Vis. (IJCV) 115(3), 330\u2013344 (2015)","journal-title":"Int. J. Comput. Vis. (IJCV)"},{"key":"22_CR19","doi-asserted-by":"crossref","unstructured":"Hershey, J.R., Chen, Z., Le Roux, J., Watanabe, S.: Deep clustering: discriminative embeddings for segmentation and separation. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2016)","DOI":"10.1109\/ICASSP.2016.7471631"},{"key":"22_CR20","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1016\/j.imavis.2016.06.004","volume":"52","author":"Y Hu","year":"2016","unstructured":"Hu, Y., Song, R., Li, Y., Rao, P., Wang, Y.: Highly accurate optical flow estimation on superpixel tree. Image Vis. Comput. 52, 167\u2013177 (2016)","journal-title":"Image Vis. Comput."},{"key":"22_CR21","unstructured":"Ioffe, S., Szegedy, C.: Batch normalization: accelerating deep network training by reducing internal covariate shift. In: International Conference on Machine Learning (ICML), pp. 448\u2013456 (2015)"},{"key":"22_CR22","doi-asserted-by":"crossref","unstructured":"Jia, Y., et al.: Caffe: convolutional architecture for fast feature embedding. In: ACM Multimedia (MM), pp. 675\u2013678 (2014)","DOI":"10.1145\/2647868.2654889"},{"key":"22_CR23","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. In: International Conference on Learning Representations (ICLR) (2015)"},{"issue":"12","key":"22_CR24","doi-asserted-by":"publisher","first-page":"2290","DOI":"10.1109\/TPAMI.2009.96","volume":"31","author":"A Levinshtein","year":"2009","unstructured":"Levinshtein, A., Stere, A., Kutulakos, K.N., Fleet, D.J., Dickinson, S.J., Siddiqi, K.: TurboPixels: fast superpixels using geometric flows. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 31(12), 2290\u20132297 (2009)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI)"},{"key":"22_CR25","unstructured":"Li, Z., Chen, J.: Superpixel segmentation using linear spectral clustering. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015)"},{"key":"22_CR26","doi-asserted-by":"crossref","unstructured":"Liu, M.Y., Tuzel, O., Ramalingam, S., Chellappa, R.: Entropy rate superpixel segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2011)","DOI":"10.1109\/CVPR.2011.5995323"},{"key":"22_CR27","doi-asserted-by":"crossref","unstructured":"Liu, Y.J., Yu, C.C., Yu, M.J., He, Y.: Manifold SLIC: a fast method to compute content-sensitive superpixels. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)","DOI":"10.1109\/CVPR.2016.77"},{"key":"22_CR28","doi-asserted-by":"crossref","unstructured":"Lu, J., Yang, H., Min, D., Do, M.N.: Patch match filter: efficient edge-aware filtering meets randomized search for fast correspondence field estimation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1854\u20131861 (2013)","DOI":"10.1109\/CVPR.2013.242"},{"issue":"11","key":"22_CR29","doi-asserted-by":"publisher","first-page":"3707","DOI":"10.1109\/TIP.2015.2451011","volume":"24","author":"V Machairas","year":"2015","unstructured":"Machairas, V., Faessel, M., C\u00e1rdenas-Pe\u00f1a, D., Chabardes, T., Walter, T., Decenci\u00e8re, E.: Waterpixels. IEEE Trans. Image Process. (TIP) 24(11), 3707\u20133716 (2015)","journal-title":"IEEE Trans. Image Process. (TIP)"},{"key":"22_CR30","doi-asserted-by":"crossref","unstructured":"Perazzi, F., Kr\u00e4henb\u00fchl, P., Pritch, Y., Hornung, A.: Saliency filters: contrast based filtering for salient region detection. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 733\u2013740 (2012)","DOI":"10.1109\/CVPR.2012.6247743"},{"key":"22_CR31","unstructured":"Rasmus, A., Berglund, M., Honkala, M., Valpola, H., Raiko, T.: Semi-supervised learning with ladder networks. In: Advances in Neural Information Processing Systems (NIPS) (2015)"},{"key":"22_CR32","unstructured":"Ren, C.Y., Prisacariu, V.A., Reid, I.D.: gSLICr: SLIC superpixels at over 250hz. arXiv preprint arXiv:1509.04232 (2015)"},{"key":"22_CR33","doi-asserted-by":"crossref","unstructured":"Ren, X., Malik, J.: Learning a classification model for segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2003)","DOI":"10.1109\/ICCV.2003.1238308"},{"key":"22_CR34","unstructured":"Sharma, A., Tuzel, O., Liu, M.Y.: Recursive context propagation network for semantic scene labeling. In: Advances in Neural Information Processing Systems (NIPS) (2014)"},{"key":"22_CR35","doi-asserted-by":"crossref","unstructured":"Shu, G., Dehghan, A., Shah, M.: Improving an object detector and extracting regions using superpixels. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3721\u20133727 (2013)","DOI":"10.1109\/CVPR.2013.477"},{"key":"22_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cviu.2017.03.007","volume":"166","author":"David Stutz","year":"2018","unstructured":"Stutz, D., Hermans, A., Leibe, B.: Superpixels: an evaluation of the state-of-the-art. Comput. Vis. Image Underst. 166(C), 1\u201327 (2018)","journal-title":"Computer Vision and Image Understanding"},{"key":"22_CR37","doi-asserted-by":"crossref","unstructured":"Sun, D., Liu, C., Pfister, H.: Local layering for joint motion estimation and occlusion detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1098\u20131105 (2014)","DOI":"10.1109\/CVPR.2014.144"},{"key":"22_CR38","doi-asserted-by":"crossref","unstructured":"Tu, W.C., et al.: Learning superpixels with segmentation-aware affinity loss. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)","DOI":"10.1109\/CVPR.2018.00066"},{"key":"22_CR39","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/978-3-642-15555-0_16","volume-title":"Computer Vision \u2013 ECCV 2010","author":"O Veksler","year":"2010","unstructured":"Veksler, O., Boykov, Y., Mehrani, P.: Superpixels and supervoxels in an energy optimization framework. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6315, pp. 211\u2013224. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-15555-0_16"},{"key":"22_CR40","unstructured":"Xie, J., Girshick, R., Farhadi, A.: Unsupervised deep embedding for clustering analysis. In: International conference on machine learning (ICML) (2016)"},{"key":"22_CR41","doi-asserted-by":"crossref","unstructured":"Yamaguchi, K., McAllester, D., Urtasun, R.: Robust monocular epipolar flow estimation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1862\u20131869 (2013)","DOI":"10.1109\/CVPR.2013.243"},{"key":"22_CR42","doi-asserted-by":"crossref","unstructured":"Yan, J., Yu, Y., Zhu, X., Lei, Z., Li, S.Z.: Object detection by labeling superpixels. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5107\u20135116 (2015)","DOI":"10.1109\/CVPR.2015.7299146"},{"key":"22_CR43","doi-asserted-by":"crossref","unstructured":"Yang, C., Zhang, L., Lu, H., Ruan, X., Yang, M.H.: Saliency detection via graph-based manifold ranking. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2013)","DOI":"10.1109\/CVPR.2013.407"},{"issue":"4","key":"22_CR44","doi-asserted-by":"publisher","first-page":"1639","DOI":"10.1109\/TIP.2014.2300823","volume":"23","author":"F Yang","year":"2014","unstructured":"Yang, F., Lu, H., Yang, M.H.: Robust superpixel tracking. IEEE Trans. Image Process. 23(4), 1639\u20131651 (2014)","journal-title":"IEEE Trans. Image Process."},{"key":"22_CR45","doi-asserted-by":"crossref","unstructured":"Yao, J., Boben, M., Fidler, S., Urtasun, R.: Real-time coarse-to-fine topologically preserving segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015)","DOI":"10.1109\/CVPR.2015.7298913"},{"key":"22_CR46","doi-asserted-by":"crossref","unstructured":"Zhu, W., Liang, S., Wei, Y., Sun, J.: Saliency optimization from robust background detection. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2014)","DOI":"10.1109\/CVPR.2014.360"}],"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\/978-3-030-01234-2_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,5]],"date-time":"2022-10-05T00:24:41Z","timestamp":1664929481000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-01234-2_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030012335","9783030012342"],"references-count":46,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-01234-2_22","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"}]}}