{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T17:40:25Z","timestamp":1790790025307,"version":"4.1.0"},"publisher-location":"Cham","reference-count":60,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031730351","type":"print"},{"value":"9783031730368","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T00:00:00Z","timestamp":1732147200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T00:00:00Z","timestamp":1732147200000},"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\/978-3-031-73036-8_13","type":"book-chapter","created":{"date-parts":[[2024,11,20]],"date-time":"2024-11-20T04:05:14Z","timestamp":1732075514000},"page":"217-235","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["CriSp: Leveraging Tread Depth Maps for\u00a0Enhanced Crime-Scene Shoeprint Matching"],"prefix":"10.1007","author":[{"given":"Samia","family":"Shafique","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shu","family":"Kong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charless","family":"Fowlkes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,11,21]]},"reference":[{"key":"13_CR1","unstructured":"6pm. http:\/\/www.6pm.com"},{"key":"13_CR2","unstructured":"Zappos. http:\/\/www.zappos.com"},{"issue":"1\u20133","key":"13_CR3","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1016\/j.forsciint.2008.07.004","volume":"181","author":"G AlGarni","year":"2008","unstructured":"AlGarni, G., Hamiane, M.: A novel technique for automatic shoeprint image retrieval. Forensic Sci. Int. 181(1\u20133), 10\u201314 (2008)","journal-title":"Forensic Sci. Int."},{"issue":"2","key":"13_CR4","doi-asserted-by":"publisher","first-page":"296","DOI":"10.3390\/sym13020296","volume":"13","author":"S Alizadeh","year":"2021","unstructured":"Alizadeh, S., Jond, H.B., Nabiyev, V.V., Kose, C.: Automatic retrieval of shoeprints using modified multi-block local binary pattern. Symmetry 13(2), 296 (2021)","journal-title":"Symmetry"},{"key":"13_CR5","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.forsciint.2017.05.025","volume":"277","author":"S Alizadeh","year":"2017","unstructured":"Alizadeh, S., Kose, C.: Automatic retrieval of shoeprint images using blocked sparse representation. Forensic Sci. Int. 277, 103\u2013114 (2017)","journal-title":"Forensic Sci. Int."},{"issue":"1","key":"13_CR6","doi-asserted-by":"publisher","first-page":"41","DOI":"10.3233\/ICA-140480","volume":"22","author":"S Almaadeed","year":"2015","unstructured":"Almaadeed, S., Bouridane, A., Crookes, D., Nibouche, O.: Partial shoeprint retrieval using multiple point-of-interest detectors and sift descriptors. Integrated Comput.-Aided Eng. 22(1), 41\u201358 (2015)","journal-title":"Integrated Comput.-Aided Eng."},{"key":"13_CR7","doi-asserted-by":"crossref","unstructured":"Arandjelovic, R., Gronat, P., Torii, A., Pajdla, T., Sivic, J.: Netvlad: Cnn architecture for weakly supervised place recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5297\u20135307 (2016)","DOI":"10.1109\/CVPR.2016.572"},{"key":"13_CR8","unstructured":"Babenko, A., Lempitsky, V.: Aggregating local deep features for image retrieval. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1269\u20131277 (2015)"},{"key":"13_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1007\/978-3-319-10590-1_38","volume-title":"Computer Vision \u2013 ECCV 2014","author":"A Babenko","year":"2014","unstructured":"Babenko, A., Slesarev, A., Chigorin, A., Lempitsky, V.: Neural codes for image retrieval. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8689, pp. 584\u2013599. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10590-1_38"},{"issue":"3","key":"13_CR10","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1016\/j.cviu.2007.09.014","volume":"110","author":"H Bay","year":"2008","unstructured":"Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (surf). Comput. Vis. Image Underst. 110(3), 346\u2013359 (2008)","journal-title":"Comput. Vis. Image Underst."},{"key":"13_CR11","unstructured":"Beis, J.S., Lowe, D.G.: Shape indexing using approximate nearest-neighbour search in high-dimensional spaces. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (1997)"},{"issue":"1","key":"13_CR12","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1177\/0049124118782533","volume":"50","author":"R Berk","year":"2021","unstructured":"Berk, R., Heidari, H., Jabbari, S., Kearns, M., Roth, A.: Fairness in criminal justice risk assessments: the state of the art. Soc. Methods Res. 50(1), 3\u201344 (2021)","journal-title":"Soc. Methods Res."},{"key":"13_CR13","doi-asserted-by":"crossref","unstructured":"Bodziak, W.J.: Footwear impression evidence: detection, recovery, and examination. CRC Press (2017)","DOI":"10.1201\/9780203755587"},{"key":"13_CR14","doi-asserted-by":"crossref","unstructured":"Bouridane, A., Alexander, A., Nibouche, M., Crookes, D.: Application of fractals to the detection and classification of shoeprints. In: Proceedings of International Conference on Image Processing, vol.\u00a01, pp. 474\u2013477 (2000)","DOI":"10.1109\/ICIP.2000.900998"},{"key":"13_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1007\/978-3-030-58565-5_4","volume-title":"Computer Vision \u2013 ECCV 2020","author":"J He","year":"2020","unstructured":"He, J., Dong, C., Qiao, Yu.: Interactive multi-dimension modulation with dynamic controllable residual learning for image restoration. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12365, pp. 53\u201368. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58565-5_4"},{"key":"13_CR16","doi-asserted-by":"crossref","unstructured":"Chowdhury, P.N., Bhunia, A.K., Sain, A., Koley, S., Xiang, T., Song, Y.Z.: Scenetrilogy: on human scene-sketch and its complementarity with photo and text. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023)","DOI":"10.1109\/CVPR52729.2023.01056"},{"key":"13_CR17","doi-asserted-by":"crossref","unstructured":"Datta, A.K., Lee, H.C., Ramotowski, R., Gaensslen, R.: Advances in fingerprint technology. CRC press (2001)","DOI":"10.1201\/9781420041347"},{"issue":"3","key":"13_CR18","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1109\/TPAMI.2005.48","volume":"27","author":"P De Chazal","year":"2005","unstructured":"De Chazal, P., Flynn, J., Reilly, R.B.: Automated processing of shoeprint images based on the fourier transform for use in forensic science. IEEE Trans. Pattern Anal. Mach. Intell. 27(3), 341\u2013350 (2005)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"13_CR19","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: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 248\u2013255 (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"13_CR20","doi-asserted-by":"crossref","unstructured":"Dey, S., Riba, P., Dutta, A., Llados, J., Song, Y.Z.: Doodle to search: practical zero-shot sketch-based image retrieval. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019)","DOI":"10.1109\/CVPR.2019.00228"},{"key":"13_CR21","doi-asserted-by":"crossref","unstructured":"Dutta, A., Akata, Z.: Semantically tied paired cycle consistency for zero-shot sketch-based image retrieval. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5089\u20135098 (2019)","DOI":"10.1109\/CVPR.2019.00523"},{"key":"13_CR22","first-page":"121","volume":"31","author":"EN Efthimiadis","year":"1996","unstructured":"Efthimiadis, E.N.: Query expansion. Annual Rev. Inform. Sci. Technol. (Arist) 31, 121\u201387 (1996)","journal-title":"Annual Rev. Inform. Sci. Technol. (Arist)"},{"key":"13_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1007\/978-3-319-46466-4_15","volume-title":"Computer Vision \u2013 ECCV 2016","author":"A Gordo","year":"2016","unstructured":"Gordo, A., Almaz\u00e1n, J., Revaud, J., Larlus, D.: Deep image retrieval: learning global representations for image search. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9910, pp. 241\u2013257. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46466-4_15"},{"key":"13_CR24","doi-asserted-by":"crossref","unstructured":"Gueham, M., Bouridane, A., Crookes, D.: Automatic recognition of partial shoeprints based on phase-only correlation. In: IEEE International Conference on Image Processing, vol.\u00a04, pp. IV\u2013441 (2007)","DOI":"10.1109\/ICIP.2007.4380049"},{"key":"13_CR25","doi-asserted-by":"crossref","unstructured":"Han, X., Leung, T., Jia, Y., Sukthankar, R., Berg, A.C.: Matchnet: unifying feature and metric learning for patch-based matching. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3279\u20133286 (2015)","DOI":"10.1109\/CVPR.2015.7298948"},{"key":"13_CR26","doi-asserted-by":"crossref","unstructured":"Hassan, M., et\u00a0al.: Deep learning model for human-intuitive shoeprint reconstruction. Expert Syst. Appli. 249, 123704 (2024)","DOI":"10.1016\/j.eswa.2024.123704"},{"key":"13_CR27","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"13_CR28","first-page":"18661","volume":"33","author":"P Khosla","year":"2020","unstructured":"Khosla, P., et al.: Supervised contrastive learning. Adv. Neural. Inf. Process. Syst. 33, 18661\u201318673 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"issue":"11","key":"13_CR29","doi-asserted-by":"publisher","first-page":"1738","DOI":"10.1007\/s11263-018-01143-3","volume":"127","author":"B Kong","year":"2019","unstructured":"Kong, B., Supancic, J., III., Ramanan, D., Fowlkes, C.C.: Cross-domain image matching with deep feature maps. Int. J. Comput. Vision 127(11), 1738\u20131750 (2019)","journal-title":"Int. J. Comput. Vision"},{"key":"13_CR30","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"498","DOI":"10.1007\/978-3-319-12484-1_57","volume-title":"Biometric Recognition","author":"X Kong","year":"2014","unstructured":"Kong, X., Yang, C., Zheng, F.: A novel method for shoeprint recognition in crime scenes. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds.) CCBR 2014. LNCS, vol. 8833, pp. 498\u2013505. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-12484-1_57"},{"key":"13_CR31","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1007\/978-3-319-16628-5_46","volume-title":"Computer Vision - ACCV 2014 Workshops","author":"A Kortylewski","year":"2015","unstructured":"Kortylewski, A., Albrecht, T., Vetter, T.: Unsupervised footwear impression analysis and retrieval from crime scene data. In: Jawahar, C.V., Shan, S. (eds.) ACCV 2014. LNCS, vol. 9008, pp. 644\u2013658. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-16628-5_46"},{"key":"13_CR32","doi-asserted-by":"crossref","unstructured":"Li, D., Li, Y., Liu, Y.: Shoeprint image retrieval based on dual attention light hash network. In: Proceedings of the 2021 4th International Conference on Artificial Intelligence and Pattern Recognition, pp. 354\u2013359 (2021)","DOI":"10.1145\/3488933.3488938"},{"key":"13_CR33","doi-asserted-by":"crossref","unstructured":"Lin, F., Li, M., Li, D., Hospedales, T., Song, Y.Z., Qi, Y.: Zero-shot everything sketch-based image retrieval, and in explainable style. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 23349\u201323358 (2023)","DOI":"10.1109\/CVPR52729.2023.02236"},{"key":"13_CR34","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60, 91\u2013110 (2004)","journal-title":"Int. J. Comput. Vision"},{"key":"13_CR35","doi-asserted-by":"publisher","first-page":"59728","DOI":"10.1109\/ACCESS.2019.2914455","volume":"7","author":"Z Ma","year":"2019","unstructured":"Ma, Z., et al.: Shoe-print image retrieval with multi-part weighted CNN. IEEE Access 7, 59728\u201359736 (2019)","journal-title":"IEEE Access"},{"issue":"1","key":"13_CR36","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1007\/s43681-022-00137-9","volume":"2","author":"MA Malek","year":"2022","unstructured":"Malek, M.A.: Criminal courts\u2019 artificial intelligence: the way it reinforces bias and discrimination. AI and Ethics 2(1), 233\u2013245 (2022)","journal-title":"AI and Ethics"},{"key":"13_CR37","doi-asserted-by":"crossref","unstructured":"Nister, D., Stewenius, H.: Scalable recognition with a vocabulary tree. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol.\u00a02, pp. 2161\u20132168 (2006)","DOI":"10.1109\/CVPR.2006.264"},{"key":"13_CR38","doi-asserted-by":"crossref","unstructured":"Noh, H., Araujo, A., Sim, J., Weyand, T., Han, B.: Large-scale image retrieval with attentive deep local features. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV), pp. 3456\u20133465 (2017)","DOI":"10.1109\/ICCV.2017.374"},{"key":"13_CR39","doi-asserted-by":"crossref","unstructured":"Pang, K., Song, Y.Z., Xiang, T., Hospedales, T.M.: Cross-domain generative learning for fine-grained sketch-based image retrieval. In: BMVC, pp. 1\u201312 (2017)","DOI":"10.5244\/C.31.46"},{"key":"13_CR40","doi-asserted-by":"crossref","unstructured":"Philbin, J., Chum, O., Isard, M., Sivic, J., Zisserman, A.: Object retrieval with large vocabularies and fast spatial matching. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.\u00a01\u20138 (2007)","DOI":"10.1109\/CVPR.2007.383172"},{"key":"13_CR41","doi-asserted-by":"crossref","unstructured":"Qian, Y., Feng, L., Song, Y., Tao, X., Chen, C.L.: Sketch me that shoe. In: IEEE Conf. Comput. Vision and Pattern Recognit.(CVPR), pp. 799\u2013807 (2016)","DOI":"10.1109\/CVPR.2016.93"},{"key":"13_CR42","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-319-46448-0_1","volume-title":"Computer Vision \u2013 ECCV 2016","author":"F Radenovi\u0107","year":"2016","unstructured":"Radenovi\u0107, F., Tolias, G., Chum, O.: CNN image retrieval learns from BoW: unsupervised fine-tuning with hard examples. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 3\u201320. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_1"},{"issue":"7","key":"13_CR43","doi-asserted-by":"publisher","first-page":"1655","DOI":"10.1109\/TPAMI.2018.2846566","volume":"41","author":"F Radenovi\u0107","year":"2018","unstructured":"Radenovi\u0107, F., Tolias, G., Chum, O.: Fine-tuning cnn image retrieval with no human annotation. IEEE Trans. Pattern Anal. Mach. Intell. 41(7), 1655\u20131668 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"13_CR44","unstructured":"Rida, I., Fei, L., Proen\u00e7a, H., Nait-Ali, A., Hadid, A.: Forensic shoe-print identification: a brief survey. arXiv preprint arXiv:1901.01431 (2019)"},{"key":"13_CR45","doi-asserted-by":"crossref","unstructured":"Sain, A., Bhunia, A.K., Chowdhury, P.N., Koley, S., Xiang, T., Song, Y.Z.: Clip for all things zero-shot sketch-based image retrieval, fine-grained or not. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2765\u20132775 (2023)","DOI":"10.1109\/CVPR52729.2023.00271"},{"key":"13_CR46","doi-asserted-by":"crossref","unstructured":"Shafique, S., Kong, B., Kong, S., Fowlkes, C.: Creating a forensic database of shoeprints from online shoe-tread photos. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 858\u2013868 (2023)","DOI":"10.1109\/WACV56688.2023.00092"},{"key":"13_CR47","doi-asserted-by":"crossref","unstructured":"Sharif\u00a0Razavian, A., Azizpour, H., Sullivan, J., Carlsson, S.: Cnn features off-the-shelf: an astounding baseline for recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 806\u2013813 (2014)","DOI":"10.1109\/CVPRW.2014.131"},{"key":"13_CR48","doi-asserted-by":"crossref","unstructured":"Song, J., Song, Y.Z., Xiang, T., Hospedales, T.M.: Fine-grained image retrieval: the text\/sketch input dilemma. In: BMVC, vol.\u00a02, p.\u00a07 (2017)","DOI":"10.5244\/C.31.45"},{"key":"13_CR49","doi-asserted-by":"crossref","unstructured":"Song, J., Yu, Q., Song, Y.Z., Xiang, T., Hospedales, T.M.: Deep spatial-semantic attention for fine-grained sketch-based image retrieval. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV), pp. 5551\u20135560 (2017)","DOI":"10.1109\/ICCV.2017.592"},{"key":"13_CR50","doi-asserted-by":"publisher","DOI":"10.1016\/j.dib.2023.109546","volume":"50","author":"A Tibben","year":"2023","unstructured":"Tibben, A., McGuire, M., Renfro, S., Carriquiry, A.: Shoecase: a data set of mock crime scene footwear impressions. Data Brief 50, 109546 (2023)","journal-title":"Data Brief"},{"key":"13_CR51","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1007\/s11263-015-0810-4","volume":"116","author":"G Tolias","year":"2016","unstructured":"Tolias, G., Avrithis, Y., J\u00e9gou, H.: Image search with selective match kernels: aggregation across single and multiple images. Int. J. Comput. Vision 116, 247\u2013261 (2016)","journal-title":"Int. J. Comput. Vision"},{"key":"13_CR52","unstructured":"Tolias, G., Sicre, R., J\u00e9gou, H.: Particular object retrieval with integral max-pooling of cnn activations. arXiv preprint arXiv:1511.05879 (2015)"},{"key":"13_CR53","doi-asserted-by":"crossref","unstructured":"Wei, C.H., Gwo, C.Y.: Alignment of core point for shoeprint analysis and retrieval. In: International Conference on Information Science, Electronics and Electrical Engineering, vol.\u00a02, pp. 1069\u20131072. IEEE (2014)","DOI":"10.1109\/InfoSEEE.2014.6947833"},{"key":"13_CR54","unstructured":"Weinzaepfel, P., Lucas, T., Larlus, D., Kalantidis, Y.: Learning super-features for image retrieval. In: International Conference on Learning Representations (2021)"},{"issue":"4","key":"13_CR55","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1016\/j.scijus.2023.04.014","volume":"63","author":"Z Wen","year":"2023","unstructured":"Wen, Z., Curran, J., Wevers, G.: Shoeprint image retrieval and crime scene shoeprint image linking by using convolutional neural network and normalized cross correlation. Sci. Justice 63(4), 439\u2013450 (2023)","journal-title":"Sci. Justice"},{"issue":"16","key":"13_CR56","doi-asserted-by":"publisher","first-page":"2487","DOI":"10.3390\/electronics11162487","volume":"11","author":"Y Wu","year":"2022","unstructured":"Wu, Y., Dong, X., Shi, G., Zhang, X., Chen, C.: Crime scene shoeprint image retrieval: A review. Electronics 11(16), 2487 (2022)","journal-title":"Electronics"},{"key":"13_CR57","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-030-01225-0_1","volume-title":"Computer Vision \u2013 ECCV 2018","author":"T Lin","year":"2018","unstructured":"Lin, T., Zhao, X., Su, H., Wang, C., Yang, M.: BSN: boundary sensitive network for temporal action proposal generation. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11208, pp. 3\u201321. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01225-0_1"},{"key":"13_CR58","doi-asserted-by":"crossref","unstructured":"Zavr\u0161nik, A.: Criminal justice, artificial intelligence systems, and human rights. In: ERA Forum, vol. 20, pp. 567\u2013583. Springer (2020)","DOI":"10.1007\/s12027-020-00602-0"},{"key":"13_CR59","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"520","DOI":"10.1007\/978-3-319-69923-3_56","volume-title":"Biometric Recognition","author":"Y Zhang","year":"2017","unstructured":"Zhang, Y., Fu, H., Dellandr\u00e9a, E., Chen, L.: Adapting convolutional neural networks on the shoeprint retrieval for forensic use. In: Zhou, J., et al. (eds.) CCBR 2017. LNCS, vol. 10568, pp. 520\u2013527. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-69923-3_56"},{"issue":"5","key":"13_CR60","doi-asserted-by":"publisher","first-page":"1224","DOI":"10.1109\/TPAMI.2017.2709749","volume":"40","author":"L Zheng","year":"2017","unstructured":"Zheng, L., Yang, Y., Tian, Q.: Sift meets cnn: a decade survey of instance retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 40(5), 1224\u20131244 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"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\/978-3-031-73036-8_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,20]],"date-time":"2024-11-20T04:53:13Z","timestamp":1732078393000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-73036-8_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,21]]},"ISBN":["9783031730351","9783031730368"],"references-count":60,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-73036-8_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,21]]},"assertion":[{"value":"21 November 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"}}]}}