Improving Target-driven Visual Navigation with Attention on 3D Spatial Relationships

V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu, “Asynchronous methods for deep reinforcement learning,” in Proc. Int. Conf. Mach. Learn. (ICML) , Jun. 2016, pp. 1928–1937

1937

Earlier work this paper cites.

S. Hochreiter and J. Schmidhuber, “Long short-term memory,” Neural Comput. , vol. 9, no. 8, pp. 1735–1780, Nov. 1997

1997

Earlier work this paper cites.

Z. Wang, T. Schaul, M. Hessel, H. Hasselt, M. Lanctot, and N. Freitas, “Dueling network architectures for deep reinforcement learning,” in Proc. Int. Conf. Mach. Learn. (ICML) , Jun. 2016, pp. 1995–2003

2003

Earlier work this paper cites.

S. Chopra, R. Hadsell, Y. LeCun et al. , “Learning a similarity metric discriminatively, with application to face verification,” in Proc. IEEE Int. Conf. Comput. Vis. Pattern Recognit. (CVPR) , Jun. 2005, pp. 539–546

2005

Earlier work this paper cites.

F. Bonin-Font, A. Ortiz, and G. Oliver, “Visual navigation for mobile robots: A survey,” J. Intell. Robotic Syst. , vol. 53, no. 3, pp. 263–296, Nov. 2008

2008

Earlier work this paper cites.

L. v. d. Maaten and G. Hinton, “Visualizing data using t-sne,” J. Mach. Learn. Res. , vol. 9, no. Nov, pp. 2579–2605, Nov. 2008

Original

2008

Earlier work this paper cites.

J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, “Imagenet: A large-scale hierarchical image database,” in Proc. IEEE Conf. Comput vis. Pattern Recognit. (CVPR) , Jun. 2009, pp. 248–255

2009

Earlier work this paper cites.

T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick, “Microsoft coco: Common objects in context,” in Proc. Eur. Conf. Comput. Vis. (ECCV) , Sep. 2014, pp. 740–755

2014

Earlier work this paper cites.

V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness, M. G. Bellemare, A. Graves, M. Riedmiller, A. K. Fidjeland, G. Ostrovski et al. , “Human-level control through deep reinforcement learning,” Nature , vol. 518, no. 7540, p. 529, Feb. 2015

2015

Earlier work this paper cites.

J. Oh, V. Chockalingam, H. Lee et al. , “Control of memory, active perception, and action in minecraft,” in Proc. Int. Conf. Mach. Learn. (ICML) , Jun. 2016, pp. 2790–2799

2016

Earlier work this paper cites.

H. Mei, M. Bansal, and M. R. Walter, “Listen, attend, and walk: Neural mapping of navigational instructions to action sequences,” in Proc. AAAI Conf. Artif. Intell. (AAAI) , Feb. 2016, pp. 2772–2778

2016

Earlier work this paper cites.

M. Kempka, M. Wydmuch, G. Runc, J. Toczek, and W. Jaśkowski, “Vizdoom: A doom-based ai research platform for visual reinforcement learning,” in Proc. IEEE Conf. Comput. Intell. Games. (CIG) , Sep. 2016, pp. 1–8

2016

Earlier work this paper cites.

C. Beattie, J. Z. Leibo, D. Teplyashin, T. Ward, M. Wainwright, H. Küttler, A. Lefrancq, S. Green, V. Valdés, A. Sadik et al. , “Deepmind lab,” 2016. [Online]. Available: https://arxiv.org/abs/1612.03801

Original

2016

Earlier work this paper cites.

T. D. Kulkarni, A. Saeedi, S. Gautam, and S. J. Gershman, “Deep successor reinforcement learning,” 2016. [Online]. Available: https://arxiv.org/abs/1606.02396

Original

2016

Earlier work this paper cites.

D. S. Chaplot, G. Lample, K. M. Sathyendra, and R. Salakhutdinov, “Transfer deep reinforcement learning in 3d environments: An empirical study,” in Proc. Adv. Neural Inf. Process. Syst. (NIPS) , Dec. 2016

2016

Earlier work this paper cites.

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. Van Den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot et al. , “Mastering the game of go with deep neural networks and tree search,” nature , vol. 529, no. 7587, p. 484, Jan. 2016

2016

Earlier work this paper cites.

T. P. Lillicrap, J. J. Hunt, A. Pritzel, N. Heess, T. Erez, Y. Tassa, D. Silver, and D. Wierstra, “Continuous control with deep reinforcement learning,” in Proc. Int. Conf. Learn. Represent. (ICLR) , Apr. 2016

2016

Earlier work this paper cites.

T. Schaul, J. Quan, I. Antonoglou, and D. Silver, “Prioritized experience replay,” in Proc. Int. Conf. Learn. Represent. (ICLR) , Apr. 2016

2016

Earlier work this paper cites.

K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Proc. IEEE Int. Conf. Comput. Vis. Pattern Recognit. (CVPR) , Jun. 2016, pp. 770–778

2016

Earlier work this paper cites.

M. Abadi, A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. S. Corrado, A. Davis, J. Dean, M. Devin et al. , “Tensorflow: Large-scale machine learning on heterogeneous distributed systems,” 2016. [Online]. Available: https://arxiv.org/abs/1603.04467

Original

2016

Earlier work this paper cites.

Y. Zhu, R. Mottaghi, E. Kolve, J. J. Lim, A. Gupta, L. Fei-Fei, and A. Farhadi, “Target-driven visual navigation in indoor scenes using deep reinforcement learning,” in Proc. IEEE Int. Conf. Rob. Autom. (ICRA) , May. 2017, pp. 3357–3364

2017

Earlier work this paper cites.

R. Krishna, Y. Zhu, O. Groth, J. Johnson, K. Hata, J. Kravitz, S. Chen, Y. Kalantidis, L.-J. Li, D. A. Shamma et al. , “Visual genome: Connecting language and vision using crowdsourced dense image annotations,” Int. J. Comput. Vis. , vol. 123, no. 1, pp. 32–73, May. 2017

2017

Cited alongside, same era.

J. Zhang, J. T. Springenberg, J. Boedecker, and W. Burgard, “Deep reinforcement learning with successor features for navigation across similar environments,” in Proc. IEEE Int. Conf. Intell. Rob. Syst. (IROS) , Sep. 2017, pp. 2371–2378

2017

Cited alongside, same era.

M. Andrychowicz, F. Wolski, A. Ray, J. Schneider, R. Fong, P. Welinder, B. McGrew, J. Tobin, O. P. Abbeel, and W. Zaremba, “Hindsight experience replay,” in Proc. Adv. Neural Inf. Process. Syst. (NIPS) , Dec. 2017, pp. 5048–5058

2017

Cited alongside, same era.

E. Kolve, R. Mottaghi, D. Gordon, Y. Zhu, A. Gupta, and A. Farhadi, “Ai2-thor: An interactive 3d environment for visual ai,” 2017. [Online]. Available: https://arxiv.org/abs/1712.05474

Original

X. Wang, W. Xiong, H. Wang, and W. Yang Wang, “Look before you leap: Bridging model-free and model-based reinforcement learning for planned-ahead vision-and-language navigation,” in Proc. Eur. Conf. Comput. Vis. (ECCV) , Sep. 2018, pp. 37–53

2018

Later among the works it cites.

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 Proc. Adv. Neural Inf. Process. Syst. (NIPS) , Dec. 2018, pp. 3314–3325

2018

Later among the works it cites.

D. Gordon, A. Kembhavi, M. Rastegari, J. Redmon, D. Fox, and A. Farhadi, “Iqa: Visual question answering in interactive environments,” in Proc. IEEE Int. Conf. Comput. Vis. Pattern Recognit. (CVPR) , Jun. 2018, pp. 4089–4098

2018

Later among the works it cites.

A. Chang, A. Dai, T. A. Funkhouser, M. Halber, M. Niebner, M. Savva, S. Song, A. Zeng, and Y. Zhang, “Matterport3d: Learning from rgb-d data in indoor environments,” in Proc. IEEE Int. Conf. 3D Vis. (3DV) , Oct. 2018, pp. 667–676