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We propose a system for rearranging objects in a scene to achieve a desired object-scene placing relationship, such as a book inserted in an open slot of a bookshelf.
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Bayesian learning via stochastic gradient langevin dynamics
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Learning structured output representation using deep conditional generative models
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Deep unsupervised learning using nonequilibrium thermodynamics
J. Sohl-Dickstein, E. Weiss, N. Maheswaranathan, and S. Ganguli · 2015
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Shapenet: An information-rich 3d model repository
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Pybullet, a python module for physics simulation for games, robotics and machine learning
E. Coumans and Y. Bai · 2016
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Human pose estimation with iterative error feedback
J. Carreira, P. Agrawal, K. Fragkiadaki, and J. Malik · 2016
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Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin · 2017
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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
C. R. Qi, L. Yi, H. Su, and L. J. Guibas · 2017
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Decoupled weight decay regularization
I. Loshchilov and F. Hutter · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
C. R. Qi, H. Su, K. Mo, and L. J. Guibas · 2017
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Deepim: Deep iterative matching for 6d pose estimation
Y. Li, G. Wang, X. Ji, Y. Xiang, and D. Fox · 2018
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A micro lie theory for state estimation in robotics
J. Sola, J. Deray, and D. Atchuthan · 2018
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Robotic pick-and-place of novel objects in clutter with multi-affordance grasping and cross-domain image matching
A. Zeng, S. Song, K.-T. Yu, E. Donlon, F. R. Hogan, M. Bauza, D. Ma, O. Taylor, M. Liu, E. Romo, et al · 2018
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Generative modeling by estimating gradients of the data distribution
Y. Song and S. Ermon · 2019
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Dynamic graph cnn for learning on point clouds
Y. Wang, Y. Sun, Z. Liu, S. E. Sarma, M. M. Bronstein, and J. M. Solomon · 2019
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On the continuity of rotation representations in neural networks
Y. Zhou, C. Barnes, J. Lu, J. Yang, and H. Li · 2019
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kpam: Keypoint affordances for category-level robotic manipulation
L. Manuelli, W. Gao, P. Florence, and R. Tedrake · 2019
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Self-supervised correspondence in visuomotor policy learning
P. Florence, L. Manuelli, and R. Tedrake · 2019
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Rearrangement: A challenge for embodied ai
D. Batra, A. X. Chang, S. Chernova, A. J. Davison, J. Deng, V. Koltun, S. Levine, J. Malik, I. Mordatch, R. Mottaghi, et al · 2020
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Denoising diffusion probabilistic models
J. Ho, A. Jain, and P. Abbeel · 2020
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Convolutional occupancy networks
S. Peng, M. Niemeyer, L. Mescheder, M. Pollefeys, and A. Geiger · 2020
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A long horizon planning framework for manipulating rigid pointcloud objects
A. Simeonov, Y. Du, B. Kim, F. R. Hogan, J. Tenenbaum, P. Agrawal, and A. Rodriguez · 2020
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Deep visual reasoning: Learning to predict action sequences for task and motion planning from an initial scene image
D. Driess, J.-S. Ha, and M. Toussaint · 2020
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Transporter networks: Rearranging the visual world for robotic manipulation
A. Zeng, P. Florence, J. Tompson, S. Welker, J. Chien, M. Attarian, T. Armstrong, I. Krasin, D. Duong, V. Sindhwani, and J. Lee · 2020
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Diffwave: A versatile diffusion model for audio synthesis
Z. Kong, W. Ping, J. Huang, K. Zhao, and B. Catanzaro · 2020
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Wavegrad: Estimating gradients for waveform generation
N. Chen, Y. Zhang, H. Zen, R. J. Weiss, M. Norouzi, and W. Chan · 2020
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Cosypose: Consistent multi-view multi-object 6d pose estimation
Y. Labbé, J. Carpentier, M. Aubry, and J. Sivic · 2020
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Contact-graspnet: Efficient 6-dof grasp generation in cluttered scenes
M. Sundermeyer, A. Mousavian, R. Triebel, and D. Fox · 2021
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Learning to regrasp by learning to place
S. Cheng, K. Mo, and L. Shao · 2021
Cited alongside, same era.
Ifor: Iterative flow minimization for robotic object rearrangement
A. Goyal, A. Mousavian, C. Paxton, Y.-W. Chao, B. Okorn, J. Deng, and D. Fox · 2022
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Structformer: Learning spatial structure for language-guided semantic rearrangement of novel objects
W. Liu, C. Paxton, T. Hermans, and D. Fox · 2022
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Semantically grounded object matching for robust robotic scene rearrangement
W. Goodwin, S. Vaze, I. Havoutis, and I. Posner · 2022
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Structdiffusion: Object-centric diffusion for semantic rearrangement of novel objects
W. Liu, T. Hermans, S. Chernova, and C. Paxton · 2022
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MIRA: Mental imagery for robotic affordances
L. Yen-Chen, P. Florence, A. Zeng, J. T. Barron, Y. Du, W.-C. Ma, A. Simeonov, A. R. Garcia, and P. Isola · 2022
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S. Thompson, L. P. Kaelbling, and T. Lozano-Perez · 2021
Cited alongside, same era.
Robotic pick-and-place with uncertain object instance segmentation and shape completion
M. Gualtieri and R. Platt · 2021
Cited alongside, same era.
Sornet: Spatial object-centric representations for sequential manipulation
W. Yuan, C. Paxton, K. Desingh, and D. Fox · 2021
Cited alongside, same era.
NeRP: Neural Rearrangement Planning for Unknown Objects
A. H. Qureshi, A. Mousavian, C. Paxton, M. Yip, and D. Fox · 2021
Cited alongside, same era.
Learning to solve sequential physical reasoning problems from a scene image
D. Driess, J.-S. Ha, and M. Toussaint · 2021
Cited alongside, same era.
Object rearrangement using learned implicit collision functions
M. Danielczuk, A. Mousavian, C. Eppner, and D. Fox · 2021
Cited alongside, same era.
O2O-Afford: Annotation-free large-scale object-object affordance learning
K. Mo, Y. Qin, F. Xiang, H. Su, and L. Guibas · 2021
Cited alongside, same era.
ReorientBot: Learning object reorientation for specific-posed placement
K. Wada, S. James, and A. J. Davison · 2022
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Equivariant Transporter Network
H. Huang, D. Wang, R. Walters, and R. Platt · 2022
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Perceiver-actor: A multi-task transformer for robotic manipulation
M. Shridhar, L. Manuelli, and D. Fox · 2022
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Neural descriptor fields: Se (3)-equivariant object representations for manipulation
A. Simeonov, Y. Du, A. Tagliasacchi, J. B. Tenenbaum, A. Rodriguez, P. Agrawal, and V. Sitzmann · 2022
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Behavior transformers: Cloning k k modes with one stone
N. M. M. Shafiullah, Z. J. Cui, A. Altanzaya, and L. Pinto · 2022
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Point-e: A system for generating 3d point clouds from complex prompts
A. Nichol, H. Jun, P. Dhariwal, P. Mishkin, and M. Chen · 2022
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Planning with diffusion for flexible behavior synthesis
M. Janner, Y. Du, J. Tenenbaum, and S. Levine · 2022
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Planning with diffusion for flexible behavior synthesis, 2022
M. Janner, Y. Du, J. B. Tenenbaum, and S. Levine · 2022
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Is conditional generative modeling all you need for decision-making?, 2022
A. Ajay, Y. Du, A. Gupta, J. Tenenbaum, T. Jaakkola, and P. Agrawal · 2022
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Megapose: 6d pose estimation of novel objects via render & compare
Y. Labbé, L. Manuelli, A. Mousavian, S. Tyree, S. Birchfield, J. Tremblay, J. Carpentier, M. Aubry, D. Fox, and J. Sivic · 2022
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Cold diffusion: Inverting arbitrary image transforms without noise
A. Bansal, E. Borgnia, H.-M. Chu, J. S. Li, H. Kazemi, F. Huang, M. Goldblum, J. Geiping, and T. Goldstein · 2022
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Elucidating the design space of diffusion-based generative models
T. Karras, M. Aittala, T. Aila, and S. Laine · 2022
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Behavior-1k: A benchmark for embodied ai with 1,000 everyday activities and realistic simulation
C. Li, R. Zhang, J. Wong, C. Gokmen, S. Srivastava, R. Martín-Martín, C. Wang, G. Levine, M. Lingelbach, J. Sun, et al · 2023
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Normalization techniques in training dnns: Methodology, analysis and application
L. Huang, J. Qin, Y. Zhou, F. Zhu, L. Liu, and L. Shao · 2023
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Se(3)-diffusionfields: Learning smooth cost functions for joint grasp and motion optimization through diffusion
J. Urain, N. Funk, J. Peters, and G. Chalvatzaki · 2023
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Lego-net: Learning regular rearrangements of objects in rooms
Q. A. Wei, S. Ding, J. J. Park, R. Sajnani, A. Poulenard, S. Sridhar, and L. Guibas · 2023
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Diffusion policy: Visuomotor policy learning via action diffusion, 2023
C. Chi, S. Feng, Y. Du, Z. Xu, E. Cousineau, B. Burchfiel, and S. Song · 2023
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Diffusion-based generation, optimization, and planning in 3d scenes
S. Huang, Z. Wang, P. Li, B. Jia, T. Liu, Y. Zhu, W. Liang, and S.-C. Zhu · 2023
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Inversion by direct iteration: An alternative to denoising diffusion for image restoration
M. Delbracio and P. Milanfar · 2023
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On the importance of noise scheduling for diffusion models
T. Chen · 2023
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Motion policy networks
A. Fishman, A. Murali, C. Eppner, B. Peele, B. Boots, and D. Fox · 2023
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