References
- P. Anderson, Q. Wu, D. Teney, J. Bruce, M. Johnson, N. Sunderhauf, I. Reid, S. Gould, and A. V. D. Hengel, "Visionand-Language Navigation: Interpreting Visually-Grounded Navigation Instructions in Real Environments," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
- X. Wang, Q. Huang, A. Celikyilmaz, J. Gao, D. Shen, Y. F. Wang, W. Y. Wang, and L. Zhang, "Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
- H. Tan, L. Yu and M. Bansal, "Learning to Navigate Unseen Environments: Back Translation with Environmental Dropout," in Proceedings of North American Chapter of the Association for Computational Linguistics (NAACL), 2019.
- A. Chang, A. Dai, T. Funkhouser, M. Halber, M. Niessner, M. Savva, S. Song, A. Zeng, and Y. Zhang, "Matterport3D: Learning from RGB-D Data in Indoor Environments," in Proceedings of the International Conference on 3D Vision, 2017.
- D. Fried, R. Hu, V. Cirik, A. Rohrbach, J. Andreas, L. P. Morency, T. Berg-Kirkpatrick, K. Saenko, D. Klein and T. Darrell, "Speaker-Follower Models for Vision-and-Language Navigation," in Proceedings of the Neural Information Processing Systems (NIPS), Vol. 28, 2018.
- W. Xiong, X. Wang, H. Wang, and W. Y. Wang, "Look Before You Leap: Bridging Model-Free and Model-Based Reinforcement Learning for Planned-Ahead Vision-and-Language Navigation," in Proceedings of the European Conference on Computer Vision (ECCV), pp. 696-711, 2018.
- G. Ilharco, V. Jain, A. Ku, E. Ie, and J. Baldridge, "General Evaluation for Instruction Conditioned Navigation using Dynamic Time Warping," in Proceedings of Neural Information Processing Systems (NeurIPS), 2019.
- M. A. Ranzato, S. Chopra, M. Auli, and W. Zaremba, "Sequence level training with recurrent neural networks." in Proceedings of the International Conference on Learning Representations (ICLR), 2015.
- R. Paulus, C. Xiong and R. Socher, "A Deep Reinforced Model for Abstractive Summarization," in Proceedings of the International Conference on Learning Representations (ICLR), 2018.
- V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu, "Asynchronous Methods for Deep Reinforcement Learning," in Proceedings of the International Conference on Machine Learning (ICML), pp. 1928-1937, 2018.
- D. J. Berndt and J. Clifford, "Using Dynamic Time Warping to Find Patterns in Time Series," in KDD Workshop, pp. 359-370, 1994.