{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T09:04:55Z","timestamp":1775552695876,"version":"3.50.1"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2019,6,21]],"date-time":"2019-06-21T00:00:00Z","timestamp":1561075200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,6,21]],"date-time":"2019-06-21T00:00:00Z","timestamp":1561075200000},"content-version":"vor","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":[[2020,3]]},"DOI":"10.1007\/s11263-019-01190-4","type":"journal-article","created":{"date-parts":[[2019,6,21]],"date-time":"2019-06-21T08:02:46Z","timestamp":1561104166000},"page":"730-741","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Convolutional Networks with Adaptive Inference Graphs"],"prefix":"10.1007","volume":"128","author":[{"given":"Andreas","family":"Veit","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Serge","family":"Belongie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,6,21]]},"reference":[{"key":"1190_CR1","unstructured":"Andreas, J., Rohrbach, M., Darrell, T., Klein, D. (2016). Learning to compose neural networks for question answering. In: Proceedings of NAACL-HLT."},{"key":"1190_CR2","unstructured":"Andreas, J., Rohrbach, M., Darrell, T., & Klein, D. (2016). Neural module networks. In: Conference on computer vision and pattern recognition (CVPR)."},{"key":"1190_CR3","unstructured":"Bengio, E., Bacon, P. L., Pineau, J., & Precup, D. (2015). Conditional computation in neural networks for faster models. arXiv preprint \narXiv:1511.06297\n\n."},{"key":"1190_CR4","unstructured":"Bengio, Y., L\u00e9onard, N., & Courville, A. (2013). Estimating or propagating gradients through stochastic neurons for conditional computation. arXiv preprint \narXiv:1308.3432\n\n."},{"key":"1190_CR5","unstructured":"Deng, J., Dong, W., Socher, R., Li, L. J., Li, K., & Fei-Fei, L. (2009). Imagenet: A large-scale hierarchical image database. In: Conference on computer vision and pattern recognition (CVPR)."},{"key":"1190_CR6","unstructured":"Figurnov, M., Collins, M. D., Zhu, Y., Zhang, L., Huang, J., Vetrov, D., & Salakhutdinov, R. (2017). Spatially adaptive computation time for residual networks. In: Conference on computer vision and pattern recognition (CVPR)."},{"key":"1190_CR7","unstructured":"Glorot, X., Bordes, A., & Bengio, Y. (2011). Deep sparse rectifier neural networks. In: International conference on artificial intelligence and statistics (AISTATS)."},{"key":"1190_CR8","unstructured":"Goodfellow, I. J., Shlens, J., & Szegedy, C. (2014). Explaining and harnessing adversarial examples. arXiv preprint \narXiv:1412.6572\n\n."},{"key":"1190_CR9","unstructured":"Gumbel, E. J. (1954). Statistical theory of extreme values and some practical applications: A series of lectures. 33. US Govt. Print. Office."},{"key":"1190_CR10","unstructured":"Guo, C., Rana, M., Cisse, M., & van\u00a0der Maaten, L. (2017). Countering adversarial images using input transformations. arXiv preprint \narXiv:1711.00117\n\n."},{"key":"1190_CR11","unstructured":"He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In: Conference on computer vision and pattern recognition (CVPR)."},{"key":"1190_CR12","unstructured":"He, K., Zhang, X., Ren, S., & Sun, J. (2016). Identity mappings in deep residual networks. In: European conference on computer vision (ECCV)."},{"key":"1190_CR13","unstructured":"Hu, J., Shen, L., & Sun, G. (2017). Squeeze-and-excitation networks. arXiv preprint \narXiv:1709.01507\n\n."},{"key":"1190_CR14","unstructured":"Huang, G., Chen, D., Li, T., Wu, F., van\u00a0der Maaten, L., & Weinberger, K. Q. (2017). Multi-scale dense convolutional networks for efficient prediction. arXiv preprint \narXiv:1703.09844\n\n."},{"key":"1190_CR15","unstructured":"Huang, G., Liu, Z., Weinberger, K. Q., & van\u00a0der Maaten, L. (2017). Densely connected convolutional networks. In: Conference on computer vision and pattern recognition (CVPR)."},{"key":"1190_CR16","doi-asserted-by":"crossref","unstructured":"Huang, G., Sun, Y., Liu, Z., Sedra, D., & Weinberger, K. Q. (2016). Deep networks with stochastic depth. In: European conference on computer vision (ECCV)","DOI":"10.1007\/978-3-319-46493-0_39"},{"key":"1190_CR17","unstructured":"Huang, X., & Belongie, S. (2017). Arbitrary style transfer in real-time with adaptive instance normalization. In: International conference on computer vision (ICCV)."},{"key":"1190_CR18","unstructured":"Ioffe, S., & Szegedy, C. (2015). Batch normalization: Accelerating deep network training by reducing internal covariate shift. In: International conference on machine learning, pp. 448\u2013456."},{"key":"1190_CR19","unstructured":"Jang, E., Gu, S., & Poole, B. (2016). Categorical reparameterization with gumbel-softmax. arXiv preprint \narXiv:1611.01144\n\n."},{"key":"1190_CR20","unstructured":"Johnson, J., Hariharan, B., van der Maaten, L., Hoffman, J., Fei-Fei, L., Zitnick, C. L., et al. (2017). Inferring andexecuting programs for visual reasoning. In: International conference on computer vision (ICCV)."},{"key":"1190_CR21","unstructured":"Kingma, D. P., & Welling, M. (2013). Auto-encoding variational bayes. arXiv preprint \narXiv:1312.6114\n\n."},{"key":"1190_CR22","unstructured":"Krizhevsky, A., & Hinton, G. (2009). Learning multiple layers of features from tiny images."},{"key":"1190_CR23","unstructured":"Li, H., Lin, Z., Shen, X., Brandt, J., & Hua, G. (2015). A convolutional neural network cascade for face detection. In: Conference on computer vision and pattern recognition (CVPR)."},{"key":"1190_CR24","doi-asserted-by":"crossref","unstructured":"Li, Y., Wang, N., Liu, J., & Hou, X. (2017). Demystifying neural style transfer. arXiv preprint \narXiv:1701.01036","DOI":"10.24963\/ijcai.2017\/310"},{"key":"1190_CR25","unstructured":"Maddison, C. J., Mnih, A., & Teh, Y. W. (2016). The concrete distribution: A continuous relaxation of discrete random variables. arXiv preprint \narXiv:1611.00712\n\n."},{"key":"1190_CR26","unstructured":"Misra, I., Gupta, A., & Hebert, M. (2017). From red wine to red tomato: Composition with context. In: Conference on computer vision and pattern recognition (CVPR)."},{"key":"1190_CR27","unstructured":"Shazeer, N., Mirhoseini, A., Maziarz, K., Davis, A., Le, Q., Hinton, G., & Dean, J. (2017). Outrageously large neural networks: The sparsely-gated mixture-of-experts layer. arXiv preprint \narXiv:1701.06538\n\n."},{"issue":"1","key":"1190_CR28","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava, N., Hinton, G. E., Krizhevsky, A., Sutskever, I., & Salakhutdinov, R. (2014). Dropout: A simple way to prevent neural networks from overfitting. Journal of machine learning research (JMLR), 15(1), 1929\u20131958.","journal-title":"Journal of machine learning research (JMLR)"},{"key":"1190_CR29","unstructured":"Srivastava, R. K., Greff, K., & Schmidhuber, J. (2015). Highway networks. arXiv preprint \narXiv:1505.00387\n\n."},{"key":"1190_CR30","unstructured":"Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., & Rabinovich, A. (2015). Going deeper with convolutions. In: Conference on computer vision and pattern recognition (CVPR)."},{"key":"1190_CR31","unstructured":"Teerapittayanon, S., McDanel, B., & Kung, H. (2016). Branchynet: Fast inference via early exiting from deep neural networks. In: Conference on pattern recognition (ICPR)."},{"key":"1190_CR32","unstructured":"Veit, A., Wilber, M. J., & Belongie, S. (2016). Residual networks behave like ensembles of relatively shallow networks. In: Advances in neural information processing systems (NIPS)."},{"issue":"2","key":"1190_CR33","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1023\/B:VISI.0000013087.49260.fb","volume":"57","author":"P Viola","year":"2004","unstructured":"Viola, P., & Jones, M. J. (2004). Robust real-time face detection. International Journal of Computer Vision (IJCV), 57(2), 137\u2013154.","journal-title":"International Journal of Computer Vision (IJCV)"},{"key":"1190_CR34","unstructured":"Yang, F., Choi, W., & Lin, Y. (2016). Exploit all the layers: Fast and accurate cnn object detector with scale dependent pooling and cascaded rejection classifiers. In: Conference on computer vision and pattern recognition (CVPR)."}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-019-01190-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11263-019-01190-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-019-01190-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,6,19]],"date-time":"2020-06-19T23:26:18Z","timestamp":1592609178000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11263-019-01190-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6,21]]},"references-count":34,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2020,3]]}},"alternative-id":["1190"],"URL":"https:\/\/doi.org\/10.1007\/s11263-019-01190-4","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"value":"0920-5691","type":"print"},{"value":"1573-1405","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,6,21]]},"assertion":[{"value":"1 February 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 June 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 June 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}