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Understanding and mapping a new environment are core abilities of any autonomously navigating agent.
Microstructure of a spatial map in the entorhinal cortex
Torkel Hafting, Marianne Fyhn, Sturla Molden, May-Britt Moser, and Edvard Moser · 2005
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Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Yarin Gal and Zoubin Ghahramani · 2014
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An empirical investigation of catastrophic forgetting in gradient-based neural networks
Ian J. Goodfellow, Mehdi Mirza, Da Xiao, Aaron Courville, and Yoshua Bengio · 2014
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Voxnet: A 3d convolutional neural network for real-time object recognition
Daniel Maturana and Sebastian Scherer · 2015
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David Ha, Andrew Dai, and Quoc V Le · 2016
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Simultaneous localization and mapping: A survey of current trends in autonomous driving
Guillaume Bresson, Zayed Alsayed, Li Yu, and Sébastien Glaser · 2017
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A point set generation network for 3d object reconstruction from a single image
Haoqiang Fan, Hao Su, and Leonidas J Guibas · 2017
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Reinforcement learning with unsupervised auxiliary tasks
Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z. Leibo, David Silver, and Koray Kavukcuoglu · 2017
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Learning to navigate in complex environments
Piotr Mirowski, Razvan Pascanu, Fabio Viola, Hubert Soyer, Andy Ballard, Andrea Banino, Misha Denil, Ross Goroshin, Laurent Sifre, Koray Kavukcuoglu, Dharshan Kumaran, and Raia Hadsell · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Target-driven visual navigation in indoor scenes using deep reinforcement learning
Yuke Zhu, Roozbeh Mottaghi, Eric Kolve, Joseph J. Lim, Abhinav Gupta, Li Fei-Fei, and Ali Farhadi · 2017
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On evaluation of embodied navigation agents
Peter Anderson, Angel X. Chang, Devendra Singh Chaplot, Alexey Dosovitskiy, Saurabh Gupta, Vladlen Koltun, Jana Kosecka, Jitendra Malik, Roozbeh Mottaghi, Manolis Savva, and Amir Roshan Zamir · 2018
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Vector-based navigation using grid-like representations in artificial agents
A. Banino, C. Barry, B. Uria, C. Blundell, T. Lillicrap, P. Mirowski, A. Pritzel, M.J. Chadwick, T. Degris, J. Modayil, G. Wayne, H. Soyer, F. Viola, B. Zhang, R. Goroshin, N. Rabinowitz, R. Pascanu, C. Beattie, S. Petersen, A. Sadik, S. Gaffney, H. King, K. Kavukcuoglu, D. Hassabis, R. Hadsell, and D. Kumaran · 2018
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Matterport3d: Learning from rgb-d data in indoor environments
Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niebner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang · 2018
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Emergence of grid-like representations by training recurrent neural networks to perform spatial localization
C.J. Cueva and X.-X. Wei · 2018
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A papier-mâché approach to learning 3d surface generation
Thibault Groueix, Matthew Fisher, Vladimir G Kim, Bryan C Russell, and Mathieu Aubry · 2018
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Mapnet: An allocentric spatial memory for mapping environments
João F. Henriques and Andrea Vedaldi · 2018
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Predicting the generalization gap in deep networks with margin distributions
Yiding Jiang, Dilip Krishnan, Hossein Mobahi, and Samy Bengio · 2018
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Neural map: Structured memory for deep reinforcement learning
Emilio Parisotto and Ruslan Salakhutdinov · 2018
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Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
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Scene memory transformer for embodied agents in long-horizon tasks
Kuan Fang, Alexander Toshev, Li Fei-Fei, and Silvio Savarese · 2019
Cited alongside, same era.
Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
Cited alongside, same era.
Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
Cited alongside, same era.
Towards task and architecture-independent generalization gap predictors
Scott Yak, Javier Gonzalvo, and Hanna Mazzawi · 2019
Cited alongside, same era.
Deep reinforcement learning on a budget: 3d control and reasoning without a supercomputer
Edward Beeching, Jilles Dibangoye, Olivier Simonin, and Christian Wolf · 2020
Cited alongside, same era.
Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data
Charles H Martin, Tongsu Serena Peng, and Michael W Mahoney · 2021
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Episodic transformer for vision-and-language navigation
A. Pashevich, C. Schmid, and C. Sun · 2021
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Rapid Exploration for Open-World Navigation with Latent Goal Models
Dhruv Shah, Benjamin Eysenbach, Nicholas Rhinehart, and Sergey Levine · 2021
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imap: Implicit mapping and positioning in real-time
Edgar Sucar, Shikun Liu, Joseph Ortiz, and Andrew J Davison · 2021
Later among the works it cites.
Neural fields in visual computing and beyond
Yiheng Xie, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, and Srinath Sridhar · 2021
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Egomap: Projective mapping and structured egocentric memory for deep RL
Edward Beeching, Jilles Dibangoye, Olivier Simonin, and Christian Wolf · 2020
Cited alongside, same era.
Learning to plan with uncertain topological maps
Edward Beeching, Jilles Dibangoye, Olivier Simonin, and Christian Wolf · 2020
Cited alongside, same era.
Object goal navigation using goal-oriented semantic exploration
Devendra Singh Chaplot, Dhiraj Gandhi, Abhinav Gupta, and Ruslan Salakhutdinov · 2020
Cited alongside, same era.
Learning to explore using active neural slam
Devendra Singh Chaplot, Dhiraj Gandhi, Saurabh Gupta, Abhinav Gupta, and Ruslan Salakhutdinov · 2020
Cited alongside, same era.
Neural topological slam for visual navigation
Devendra Singh Chaplot, Ruslan Salakhutdinov, Abhinav Gupta, and Saurabh Gupta · 2020
Cited alongside, same era.
gradSLAM: Automagically differentiable SLAM
Krishna Murthy Jatavallabhula, Soroush Saryazdi, Ganesh Iyer, and Liam Paull · 2020
Cited alongside, same era.
Heavy-tailed universality predicts trends in test accuracies for very large pre-trained deep neural networks
Charles H Martin and Michael W Mahoney · 2020
Cited alongside, same era.
In-place scene labelling and understanding with implicit scene representation
Shuaifeng Zhi, Tristan Laidlow, Stefan Leutenegger, and Andrew J Davison · 2021
Later among the works it cites.
ilabel: Interactive neural scene labelling
Shuaifeng Zhi, Edgar Sucar, Andre Mouton, Iain Haughton, Tristan Laidlow, and Andrew J Davison · 2021
Later among the works it cites.
Vision-only robot navigation in a neural radiance world
Michal Adamkiewicz, Timothy Chen, Adam Caccavale, Rachel Gardner, Preston Culbertson, Jeannette Bohg, and Mac Schwager · 2022
Closest in time.
Think Global, Act Local: Dual-scale Graph Transformer for Vision-and-Language Navigation
Shizhe Chen, Pierre-Louis Guhur, Makarand Tapaswi, Cordelia Schmid, and Ivan Laptev · 2022
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Learning Continuous Environment Fields via Implicit Functions
Xueting Li, Shalini De Mello, Xiaolong Wang, Ming-Hsuan Yang, Jan Kautz, and Sifei Liu · 2022
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3d neural scene representations for visuomotor control
Yunzhu Li, Shuang Li, Vincent Sitzmann, Pulkit Agrawal, and Antonio Torralba · 2022
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Teaching agents how to map: Spatial reasoning for multi-object navigation
Pierre Marza, Laetitia Matignon, Olivier Simonin, and Christian Wolf · 2022
Closest in time.
iSDF: Real-Time Neural Signed Distance Fields for Robot Perception
Joseph Ortiz, Alexander Clegg, Jing Dong, Edgar Sucar, David Novotny, Michael Zollhoefer, and Mustafa Mukadam · 2022
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Neural implicit flow: a mesh-agnostic dimensionality reduction paradigm of spatio-temporal data
Shaowu Pan, Steven L Brunton, and J Nathan Kutz · 2022
Closest in time.
Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, and Nando de Freitas · 2022
Closest in time.
Hypertransformer: Model generation for supervised and semi-supervised few-shot learning
Andrey Zhmoginov, Mark Sandler, and Max Vladymyrov · 2022
Closest in time.
Nice-slam: Neural implicit scalable encoding for slam
Zihan Zhu, Songyou Peng, Viktor Larsson, Weiwei Xu, Hujun Bao, Zhaopeng Cui, Martin R Oswald, and Marc Pollefeys · 2022
Closest in time.
G. Bono, L. Antsfeld, A. Sadek, G. Monaci, and C. Wolf · 2023
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Orbeez-slam: A real-time monocular visual slam with orb features and nerf-realized mapping
Chi-Ming Chung, Yang-Che Tseng, Ya-Ching Hsu, Xiang-Qian Shi, Yun-Hung Hua, Jia-Fong Yeh, Wen-Chin Chen, Yi-Ting Chen, and Winston H Hsu · 2023
Closest in time.
Learning whom to trust in navigation: dynamically switching between classical and neural planning
S. Dey, A. Sadek, G. Monaci, B. Chidlovskii, and C. Wolf · 2023
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Multi-Object Navigation in real environments using hybrid policies
A. Sadek, G. Bono, B. Chidlovskii, A. Baskurt, and C. Wolf · 2023
Closest in time.