{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T19:59:09Z","timestamp":1770667149925,"version":"3.49.0"},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2018,7,6]],"date-time":"2018-07-06T00:00:00Z","timestamp":1530835200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Comput Vis"],"published-print":{"date-parts":[[2018,9]]},"DOI":"10.1007\/s11263-018-1108-0","type":"journal-article","created":{"date-parts":[[2018,7,6]],"date-time":"2018-07-06T08:58:56Z","timestamp":1530867536000},"page":"899-901","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["The Reasonable Effectiveness of Synthetic Visual Data"],"prefix":"10.1007","volume":"126","author":[{"given":"Adrien","family":"Gaidon","sequence":"first","affiliation":[]},{"given":"Antonio","family":"Lopez","sequence":"additional","affiliation":[]},{"given":"Florent","family":"Perronnin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,7,6]]},"reference":[{"key":"1108_CR1","doi-asserted-by":"crossref","unstructured":"Butler, D., Wulff, J., Stanley, G.\u00a0B., & Black, M.\u00a0J. (2012). A naturalistic open source movie for optical flow evaluation. In Proceedings of the European conference on computer vision.","DOI":"10.1007\/978-3-642-33783-3_44"},{"key":"1108_CR2","doi-asserted-by":"crossref","unstructured":"Chen, C., Seff, A., Kornhauser, A., & Xiao, J. (2015). DeepDriving: Learning affordance for direct perception in autonomous driving. In Proceedings of the international conference on computer vision.","DOI":"10.1109\/ICCV.2015.312"},{"key":"1108_CR3","doi-asserted-by":"crossref","unstructured":"Cordts, M., Omran, M., Ramos, S., Rehfeld, T., Enzweiler, M., Benenson, R., et al. (2016). The Cityscapes dataset for semantic urban scene understanding. In Proceedings of the conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR.2016.350"},{"key":"1108_CR4","doi-asserted-by":"crossref","unstructured":"de Souza, C., Gaidon, A., Cabon, Y., & L\u00f3pez, A. (2017). Procedural generation of videos to train deep action recognition networks. In Proceedings of the conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR.2017.278"},{"key":"1108_CR5","unstructured":"Dosovitskiy, A., Ros, G., Codevilla, F., Lopez, A., & Koltun, V. (2017). CARLA: An open urban driving simulator. In Proceedings of the conference on robot learning."},{"key":"1108_CR6","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s11263-009-0275-4","volume":"88","author":"M Everingham","year":"2010","unstructured":"Everingham, M., Gool, L. V., Williams, C., Winn, J., & Zisserman, A. (2010). The Pascal visual object classes (VOC) challenge. International Journal of Computer Vision, 88, 303\u2013338.","journal-title":"International Journal of Computer Vision"},{"key":"1108_CR7","unstructured":"Gaidon, A., Wang, Q., Cabon, Y., & Vig, R. (2016). Virtual worlds as proxy for multi-object tracking analysis. In Proceedings of the conference on computer vision and pattern recognition."},{"key":"1108_CR8","doi-asserted-by":"crossref","unstructured":"Geiger, A., Lenz, P., & Urtasun, R. (2012). Are we ready for autonomous driving? The KITTI vision benchmark suite. In Proceedings of the conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR.2012.6248074"},{"key":"1108_CR9","unstructured":"Handa, A., Patraucean, V., Badrinarayanan, V., Stent, S., & Cipolla, R. (2016). Understanding real world indoor scenes with synthetic data. In Proceedings of the conference on computer vision and pattern recognition."},{"key":"1108_CR10","unstructured":"Hestness, J., Narang, S., Ardalani, N., Diamos, G., Jun, H., Kianinejad, H., et al. (2017). Deep learning scaling is predictable, empirically. arXiv preprint \n                    arXiv:1712.00409\n                    \n                  ."},{"key":"1108_CR11","doi-asserted-by":"crossref","unstructured":"Johnson-Roberson, M., Barto, C., Mehta, R., Sridhar, S., Rosaen, K., & Vasudevan, R. (2017). Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks? In Proceedings of the IEEE international conference on robotics and automation.","DOI":"10.1109\/ICRA.2017.7989092"},{"key":"1108_CR12","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521, 436\u2013444.","journal-title":"Nature"},{"key":"1108_CR13","unstructured":"Li, X., Wang, K., Tian, Y., Yan, L., & Wang, F.-Y. (2017). The ParallelEye dataset: Constructing large-scale artificial scenes for traffic vision research. In Proceedings of the IEEE international conference on intelligent transportation systems."},{"key":"1108_CR14","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., et al.. (2014). Microsoft COCO: Common objects in context. In Proceedings of the European conference on computer vision.","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"1108_CR15","doi-asserted-by":"crossref","unstructured":"Mayer, N., Ilg, E., Hausser, P., Fischer, P., Cremers, D., Dosovitskiy, A., et al. (2016). A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation. In Proceedings of the conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR.2016.438"},{"key":"1108_CR16","doi-asserted-by":"crossref","unstructured":"Richter, S., Hayder, Z., & Koltun, V. (2017). Playing for benchmarks. In Proceedings of the international conference on computer vision.","DOI":"10.1109\/ICCV.2017.243"},{"key":"1108_CR17","doi-asserted-by":"crossref","unstructured":"Ros, G., Sellart, L., Materzyska, J., V\u00e1zquez, D., & L\u00f3pez, A. (2016). The SYNTHIA dataset: A large collection of synthetic images for semantic segmentation of urban scenes. In Proceedings of the conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR.2016.352"},{"issue":"3","key":"1108_CR18","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., et al. (2015). ImageNet large scale visual recognition challenge. International Journal of Computer Vision, 115(3), 211\u2013252.","journal-title":"International Journal of Computer Vision"},{"key":"1108_CR19","unstructured":"Savva, M., Chang, A., D.\u00a0A., Funkhouser, T., & Koltun, V. (2017). MINOS: Multimodal indoor simulator for navigation in complex environments. \n                    arXiv:1712.03931\n                    \n                  ."},{"key":"1108_CR20","unstructured":"Shah, S., Dey, D., Lovett, C., & Kapoor, A. (2017). AirSim: High-fidelity visual and physical simulation for autonomous vehicles. In Proceedings of the field and service robotics."},{"key":"1108_CR21","doi-asserted-by":"crossref","unstructured":"Sun, C., Shrivastava, A., Singh, S., & Gupta, A. (2017). Revisiting unreasonable effectiveness of data in deep learning era. In 2017 IEEE international conference on computer vision (ICCV) (pp.\u00a0843\u2013852). IEEE.","DOI":"10.1109\/ICCV.2017.97"}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11263-018-1108-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-018-1108-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-018-1108-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,5]],"date-time":"2019-07-05T23:18:13Z","timestamp":1562368693000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11263-018-1108-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,6]]},"references-count":21,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2018,9]]}},"alternative-id":["1108"],"URL":"https:\/\/doi.org\/10.1007\/s11263-018-1108-0","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"value":"0920-5691","type":"print"},{"value":"1573-1405","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,7,6]]},"assertion":[{"value":"6 July 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}