BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments
暂无分享,去创建一个
Silvio Savarese | C. Karen Liu | Li Fei-Fei | Hyowon Gweon | C. K. Liu | Shyamal Buch | Michael Lingelbach | Cem Gokmen | Kent Vainio | Chengshu Li | Fei Xia | Roberto Mart'in-Mart'in | Sanjana Srivastava | Jiajun Wu | Zheng Lian | Li Fei-Fei | S. Savarese | Hyowon Gweon | S. Buch | Fei Xia | Chengshu Li | Jiajun Wu | Roberto Mart'in-Mart'in | Kent Vainio | Zheng Lian | Michael Lingelbach | Cem Gokmen | S. Srivastava | C. Liu
[1] Sanjiv Singh,et al. The DARPA Urban Challenge: Autonomous Vehicles in City Traffic, George Air Force Base, Victorville, California, USA , 2009, The DARPA Urban Challenge.
[2] Dana H. Ballard,et al. Animate Vision , 1991, Artif. Intell..
[3] Sridhar Mahadevan,et al. Recent Advances in Hierarchical Reinforcement Learning , 2003, Discret. Event Dyn. Syst..
[4] Danica Kragic,et al. Trends and challenges in robot manipulation , 2019, Science.
[5] Luca Iocchi,et al. RoboCup@Home: Scientific Competition and Benchmarking for Domestic Service Robots , 2009 .
[6] Tsuyoshi Murata,et al. {m , 1934, ACML.
[7] Alec Radford,et al. Proximal Policy Optimization Algorithms , 2017, ArXiv.
[8] Andrew J. Davison,et al. RLBench: The Robot Learning Benchmark & Learning Environment , 2019, IEEE Robotics and Automation Letters.
[9] Joonho Lee,et al. Learning agile and dynamic motor skills for legged robots , 2019, Science Robotics.
[10] Sergey Levine,et al. Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning , 2019, CoRL.
[11] Alexander Lerchner,et al. COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration , 2019, ArXiv.
[12] Bernard Ghanem,et al. ActivityNet: A large-scale video benchmark for human activity understanding , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[13] Marcin Andrychowicz,et al. Solving Rubik's Cube with a Robot Hand , 2019, ArXiv.
[14] Ali Farhadi,et al. OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[15] Roozbeh Mottaghi,et al. ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Jana Kosecka,et al. Visual Representations for Semantic Target Driven Navigation , 2018, 2019 International Conference on Robotics and Automation (ICRA).
[17] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[18] Sergey Levine,et al. Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations , 2017, Robotics: Science and Systems.
[19] Sergey Levine,et al. Generalization through Simulation: Integrating Simulated and Real Data into Deep Reinforcement Learning for Vision-Based Autonomous Flight , 2019, 2019 International Conference on Robotics and Automation (ICRA).
[20] Sergey Levine,et al. Learning to Walk via Deep Reinforcement Learning , 2018, Robotics: Science and Systems.
[21] Michael S. Bernstein,et al. Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations , 2016, International Journal of Computer Vision.
[22] Roozbeh Mottaghi,et al. Visual Room Rearrangement , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Katharina Rifai,et al. Accuracy and precision of the HTC VIVE PRO eye tracking in head-restrained and head-free conditions , 2020 .
[24] Leslie Pack Kaelbling,et al. FFRob: An Efficient Heuristic for Task and Motion Planning , 2015, WAFR.
[25] Pieter Abbeel,et al. Learning to Manipulate Deformable Objects without Demonstrations , 2019, Robotics: Science and Systems.
[26] Ali Farhadi,et al. AI2-THOR: An Interactive 3D Environment for Visual AI , 2017, ArXiv.
[27] Joshua B. Tenenbaum,et al. The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark Towards Physically Realistic Embodied AI , 2021, 2022 International Conference on Robotics and Automation (ICRA).
[28] Silvio Savarese,et al. HRL4IN: Hierarchical Reinforcement Learning for Interactive Navigation with Mobile Manipulators , 2019, CoRL.
[29] Roberto Mart'in-Mart'in,et al. robosuite: A Modular Simulation Framework and Benchmark for Robot Learning , 2020, ArXiv.
[30] Silvio Savarese,et al. Deep Visual MPC-Policy Learning for Navigation , 2019, IEEE Robotics and Automation Letters.
[31] P. Cochat,et al. Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.
[32] Silvio Savarese,et al. Interactive Gibson Benchmark: A Benchmark for Interactive Navigation in Cluttered Environments , 2020, IEEE Robotics and Automation Letters.
[33] Jitendra Malik,et al. Combining Optimal Control and Learning for Visual Navigation in Novel Environments , 2019, CoRL.
[34] Dieter Fox,et al. PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes , 2017, Robotics: Science and Systems.
[35] Sergey Levine,et al. From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following , 2019, ICLR.
[36] Sergey Levine,et al. Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor , 2018, ICML.
[37] Yiannis Aloimonos,et al. Active vision , 2004, International Journal of Computer Vision.
[38] Rahul Sukthankar,et al. Cognitive Mapping and Planning for Visual Navigation , 2017, International Journal of Computer Vision.
[39] Stefan Lee,et al. Embodied Question Answering , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[40] Oliver Brock,et al. Lessons from the Amazon Picking Challenge: Four Aspects of Building Robotic Systems , 2016, IJCAI.
[41] Dan Klein,et al. Speaker-Follower Models for Vision-and-Language Navigation , 2018, NeurIPS.
[42] Danna Zhou,et al. d. , 1840, Microbial pathogenesis.
[43] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[44] Silvio Savarese,et al. JRDB: A Dataset and Benchmark of Egocentric Robot Visual Perception of Humans in Built Environments , 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[45] Silvio Savarese,et al. iGibson 1.0: A Simulation Environment for Interactive Tasks in Large Realistic Scenes , 2020, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[46] Victor Talpaert,et al. Deep Reinforcement Learning for Autonomous Driving: A Survey , 2020, IEEE Transactions on Intelligent Transportation Systems.
[47] Jitendra Malik,et al. Habitat: A Platform for Embodied AI Research , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[48] Andreas Geiger,et al. Are we ready for autonomous driving? The KITTI vision benchmark suite , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[49] Susanne Westphal,et al. The “Something Something” Video Database for Learning and Evaluating Visual Common Sense , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[50] Xinlei Chen,et al. Multi-Target Embodied Question Answering , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[51] Yolanda Gil,et al. Description Logics and Planning , 2005, AI Mag..
[52] David Held,et al. SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation , 2020, CoRL.
[53] Sanja Fidler,et al. VirtualHome: Simulating Household Activities Via Programs , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[54] Rahul Sukthankar,et al. Cognitive Mapping and Planning for Visual Navigation , 2017, International Journal of Computer Vision.
[55] Craig A. Knoblock,et al. PDDL-the planning domain definition language , 1998 .
[56] Yuan-Fang Wang,et al. Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[57] Thomas de Quincey. [C] , 2000, The Works of Thomas De Quincey, Vol. 1: Writings, 1799–1820.
[58] Hiroaki Kitano,et al. RoboCup: A Challenge Problem for AI , 1997, AI Mag..
[59] Silvio Savarese,et al. Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[60] P. Alam. ‘T’ , 2021, Composites Engineering: An A–Z Guide.
[61] R. Sarpong,et al. Bio-inspired synthesis of xishacorenes A, B, and C, and a new congener from fuscol† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c9sc02572c , 2019, Chemical science.
[62] Tom Schaul,et al. FeUdal Networks for Hierarchical Reinforcement Learning , 2017, ICML.
[63] MahadevanSridhar,et al. Recent Advances in Hierarchical Reinforcement Learning , 2003 .
[64] Oliver Brock,et al. Interactive Perception: Leveraging Action in Perception and Perception in Action , 2016, IEEE Transactions on Robotics.
[65] Silvio Savarese,et al. ReLMoGen: Leveraging Motion Generation in Reinforcement Learning for Mobile Manipulation , 2020, ArXiv.
[66] Christopher Kanan,et al. Gaze-in-wild: A dataset for studying eye and head coordination in everyday activities , 2019, Scientific Reports.
[67] Jitendra Malik,et al. Gibson Env: Real-World Perception for Embodied Agents , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[68] Mehmet R. Dogar,et al. Mobile Manipulation Hackathon: Moving into Real World Applications , 2021, IEEE Robotics & Automation Magazine.
[69] Alejandro Perez,et al. Optimal Bidirectional Rapidly-Exploring Random Trees , 2013 .
[70] Joseph J. Lim,et al. IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks , 2019, 2021 IEEE International Conference on Robotics and Automation (ICRA).
[71] Wojciech Zaremba,et al. OpenAI Gym , 2016, ArXiv.
[72] Leonidas J. Guibas,et al. SAPIEN: A SimulAted Part-Based Interactive ENvironment , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[73] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.
[74] Cordelia Schmid,et al. Actor and Observer: Joint Modeling of First and Third-Person Videos , 2018, CVPR.
[75] Oliver Brock,et al. Analysis and Observations From the First Amazon Picking Challenge , 2016, IEEE Transactions on Automation Science and Engineering.
[76] Javier Ruiz-del-Solar,et al. RoboCup@Home: Analysis and results of evolving competitions for domestic and service robots , 2015, Artif. Intell..
[77] Larry Jackel,et al. The DARPA Robotics Challenge Finals: Results and Perspectives , 2017, J. Field Robotics.
[78] Wojciech M. Czarnecki,et al. Grandmaster level in StarCraft II using multi-agent reinforcement learning , 2019, Nature.
[79] Stefan Lee,et al. Neural Modular Control for Embodied Question Answering , 2018, CoRL.
[80] K. K. Nambiar,et al. Foundations of Computer Science , 2001, Lecture Notes in Computer Science.
[81] Jakub W. Pachocki,et al. Learning dexterous in-hand manipulation , 2018, Int. J. Robotics Res..
[82] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[83] Joanna Isabelle Olszewska,et al. A review and comparison of ontology-based approaches to robot autonomy , 2019, The Knowledge Engineering Review.