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Jason J. Corso
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[1] S. Kumar, V. Dhiman, P. Koch, and J. J. Corso. Learning compositional sparse bimodal models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(5):1032--1044, 2018. [ bib | DOI | code ]
[2] K. R. Keane and J. J. Corso. The wrong tool for inference --- a critical view of gaussian graphical models. In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods, 2018. [ bib ]
[3] L. Zhou, C. Xu, and J. J. Corso. Towards automatic learning of procedures from web instructional videos. In Proceedings of AAAI Conference on Artificial Intelligence, 2018. [ bib | code | data | http ]
[4] L. Zhou, Y. Zhou, J. J. Corso, R. Socher, and C. Xiong. End-to-end dense video captioning with masked transformer. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2018. [ bib | code | .pdf ]
[5] X. Sun, R. Szeto, and J. J. Corso. A Temporally-Aware Interpolation Network for Video Frame Inpainting. In Proceedings of Asian Conference on Computer Vision (ACCV), 2018. [ bib | code | project | http ]
[6] L. Zhou, N. Louis, and J. J. Corso. Weakly-supervised video object grounding from text by loss weighting and object interaction. In Proceedings of British Machine Vision Conference, 2018. [ bib | .pdf ]
[7] R. Szeto, S. Stent, G. Ros, and J. J. Corso. A dataset to evaluate the representations learned by video prediction models. Technical report, ICLR Workshops, 2018. [ bib | code | project | http ]
[8] A. Venkataraman, B. Griffin, and J. J. Corso. Learning kinematic descriptions using spare: Simulated and physical ARticulated extendable dataset. Technical Report 1803.11147, ARXIV, 2018. [ bib | http ]
[9] V. Dhiman, S. Banerjee, B. Griffin, J. M. Siskind, and J. J. Corso. A critical investigation of deep reinforcement learning for navigation. Technical Report 1802.02274, ARXIV, 2018. [ bib | http ]
[10] S. Patel, B. Griffin, K. Kusano, and J. J. Corso. Predicting future lane changes of other highway vehicles using rnn-based deep models. Technical Report 1801.04340, ARXIV, 2018. [ bib | http ]
[11] M. R. Ganesh, E. Hofesmann, B. Min, N. Gafoor, and J. J. Corso. T-recs: Training for rate-invariant embeddings by controlling speed for action recognition. Technical Report 1803.08094, ARXIV, 2018. [ bib | http ]
[12] E. Hofesmann, M. R. Ganesh, and J. J. Corso. M-PACT: An open source platform for repeatable activity classification research. Technical Report 1804.05879, ARXIV, 2018. [ bib | code | http ]
[13] M. El Banani and J. J. Corso. Adviser networks: Learning what question to ask for human-in-the-loop viewpoint estimation. Technical Report 1802.01666, ARXIV, 2018. [ bib | code | http ]

last updated: Wed Dec 11 11:05:29 2019; copyright jcorso
Please report broken links to Prof. Corso jjcorso@eecs.umich.edu .