jcorso_fullstripped.bib

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@techreport{ElCoARXIV2018,
  author = {{El Banani}, M. and {\bf Corso}, {\bf J. J.}},
  codedownload = {https://github.com/mbanani/adviser_networks},
  institution = {ARXIV},
  number = {1802.01666},
  tags = {computer vision, human-in-the-loop, deep learning, viewpoint estimation},
  title = {Adviser Networks: Learning What Question to Ask for Human-In-The-Loop Viewpoint Estimation},
  url = {https://arxiv.org/abs/1802.01666},
  year = {2018}
}

@techreport{HoGaCoARXIV2018,
  author = {Hofesmann, E. and Ganesh, M. R. and {\bf Corso}, {\bf J. J.}},
  codedownload = {https://github.com/MichiganCOG/M-PACT},
  institution = {ARXIV},
  number = {1804.05879},
  tags = {computer vision, video understanding, deep learning, activity recognition},
  title = {{M-PACT}: An Open Source Platform for Repeatable Activity Classification Research},
  url = {https://arxiv.org/abs/1804.05879},
  year = {2018}
}

@techreport{GaHoMiARXIV2018,
  author = {Ganesh, M. R. and Hofesmann, E. and Min, B. and Gafoor, N. and {\bf Corso}, {\bf J. J.}},
  institution = {ARXIV},
  number = {1803.08094},
  tags = {computer vision, video understanding, deep learning, activity recognition},
  title = {T-RECS: Training for Rate-Invariant Embeddings by Controlling Speed for Action Recognition},
  url = {https://arxiv.org/abs/1803.08094},
  year = {2018}
}

@techreport{PaGrKuARXIV2018,
  author = {Patel, S. and Griffin, B. and Kusano, K. and {\bf Corso}, {\bf J. J.}},
  institution = {ARXIV},
  number = {1801.04340},
  tags = {deep learning, action prediction, autonomous driving},
  title = {Predicting Future Lane Changes of Other Highway Vehicles using RNN-based Deep Models},
  url = {https://arxiv.org/abs/1801.04340},
  year = {2018}
}

@techreport{DhBaGrARXIV2018,
  author = {Dhiman, V. and Banerjee, S. and Griffin, B. and Siskind, J. M. and {\bf Corso}, {\bf J. J.}},
  institution = {ARXIV},
  number = {1802.02274},
  tags = {deep reinforcement learning, navigation, robotics},
  title = {A Critical Investigation of Deep Reinforcement Learning for Navigation},
  url = {https://arxiv.org/abs/1802.02274},
  year = {2018}
}

@techreport{VeGrCoARXIV2018,
  author = {Venkataraman, A. and Griffin, B. and {\bf Corso}, {\bf J. J.}},
  institution = {ARXIV},
  number = {1803.11147},
  title = {Learning Kinematic Descriptions using SPARE: Simulated and Physical {AR}ticulated Extendable dataset},
  url = {https://arxiv.org/abs/1803.11147},
  year = {2018}
}

@techreport{SzStRoICLRW2018,
  author = {Szeto, R. and Stent, S. and Ros, G. and {\bf Corso}, {\bf J. J.}},
  codedownload = {https://github.com/rszeto/moving-symbols},
  institution = {ICLR Workshops},
  projectpage = {http://ryanszeto.com/projects/moving-symbols.html},
  title = {A Dataset to Evaluate The Representations Learned by Video Prediction Models},
  url = {https://arxiv.org/abs/1802.08936},
  year = {2018}
}

@inproceedings{ZhLoCoBMVC2018,
  author = {Zhou, L. and Louis, N. and {\bf Corso}, {\bf J. J.}},
  booktitle = {Proceedings of British Machine Vision Conference},
  tags = {video understanding, video to text, computer vision, object grounding, deep learning},
  title = {Weakly-Supervised Video Object Grounding from Text by Loss Weighting and Object Interaction},
  url = {http://bmvc2018.org/contents/papers/0070.pdf},
  year = {2018}
}

@inproceedings{SuSzCoACCV2018,
  author = {Sun, X. and Szeto, R. and {\bf Corso}, {\bf J. J.}},
  booktitle = {Proceedings of Asian Conference on Computer Vision (ACCV)},
  codedownload = {https://github.com/sunxm2357/TAI_video_frame_inpainting},
  projectpage = {http://ryanszeto.com/projects/tai.html},
  tags = {video understanding, deep learning, computer vision, video prediction, inpainting},
  title = {{A Temporally-Aware Interpolation Network for Video Frame Inpainting}},
  url = {https://arxiv.org/abs/1803.07218},
  year = {2018}
}

@inproceedings{ZhZhCoCVPR2018,
  author = {Zhou, L. and Zhou, Y. and {\bf Corso}, {\bf J. J.} and Socher, R. and Xiong, C.},
  booktitle = {{Proceedings of IEEE Conference on Computer Vision and Pattern Recognition}},
  codedownload = {https://github.com/LuoweiZhou/densecap},
  tags = {video understanding, computer vision, video to text},
  title = {End-to-End Dense Video Captioning with Masked Transformer},
  url = {http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhou_End-to-End_Dense_Video_CVPR_2018_paper.pdf},
  year = {2018}
}

@inproceedings{ZhXuCoAAAI2018,
  author = {Zhou, L. and Xu, C. and {\bf Corso}, {\bf J. J.}},
  booktitle = {Proceedings of AAAI Conference on Artificial Intelligence},
  codedownload = {https://github.com/LuoweiZhou/ProcNets-YouCook2},
  datadownload = {http://youcook2.eecs.umich.edu},
  tags = {video to text, video understanding},
  title = {Towards Automatic Learning of Procedures from Web Instructional Videos},
  url = {https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/17344/16367},
  year = {2018}
}

@inproceedings{KeCoICPRAM2018,
  author = {Keane, K. R. and {\bf Corso}, {\bf J. J.}},
  booktitle = {Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods},
  tags = {graphical models, inference},
  title = {The Wrong Tool for Inference --- A Critical View of Gaussian Graphical Models},
  year = {2018}
}

@article{KuDhKoTPAMI2018,
  author = {Kumar, S. and Dhiman, V. and Koch, P. and {\bf Corso}, {\bf J. J.}},
  codedownload = {https://bitbucket.org/surenkum/bimodal_sparse},
  doi = {10.1109/TPAMI.2017.2693987},
  journal = {{IEEE Transactions on Pattern Analysis and Machine Intelligence}},
  number = {5},
  pages = {1032--1044},
  tags = {artificial intelligence, language grounding, computer vision, cognitive systems},
  title = {Learning Compositional Sparse Bimodal Models},
  volume = {40},
  year = {2018}
}