Fetching the paper…
Reading the bibliography…
Point clouds are a widely available and canonical data modality which convey the 3D geometry of a scene.
Determining Optical Flow
B. K. Horn and B. G. Schunck · 1980
Earlier work this paper cites.
Efficient Training of Artificial Neural Networks for Autonomous Navigation
D. A. Pomerleau · 1991
Earlier work this paper cites.
Noise and the Reality Gap: The use of Simulation in Evolutionary Robotics
N. Jakobi, P.Husbands, and I. Harvey · 1995
Earlier work this paper cites.
Three-dimensional Scene Flow
S. Vedula, S. Baker, P. Rander, R. Collins, and T. Kanade · 1999
Earlier work this paper cites.
A Survey of Robot Learning From Demonstration
B. D. Argall, S. Chernova, M. Veloso, and B. Browning · 2009
Earlier work this paper cites.
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
S. Ross, G. J. Gordon, and J. A. Bagnell · 2011
Earlier work this paper cites.
Online Movement Adaptation Based on Previous Sensor Experiences
P. Pastor, L. Righetti, M. Kalakrishnan, and S. Schaal · 2011
Earlier work this paper cites.
Learning Articulated Motions From Visual Demonstration
S. Pillai, M. R. Walter, and S. Teller · 2014
Earlier work this paper cites.
Unified Particle Physics for Real-Time Applications
M. Macklin, M. Muller, N. Chentanez, and T.-Y. Kim · 2014
Earlier work this paper cites.
FlowNet: Learning Optical Flow with Convolutional Networks
P. Fischer, A. Dosovitskiy, E. Ilg, P. Hausser, C. Hazırbaş, V. Golkov, P. van der Smagt, D. Cremers, and T. Brox · 2015
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization
D. P. Kingma and J. Ba · 2015
Earlier work this paper cites.
End-to-end Training of Deep Visuomotor Policies
S. Levine, C. Finn, T. Darrell, and P. Abbeel · 2016
Earlier work this paper cites.
Supersizing Self-supervision: Learning to Grasp from 50K Tries and 700 Robot Hours
L. Pinto and A. Gupta · 2016
Earlier work this paper cites.
Towards Learning to Perceive and Reason About Liquids
C. Schenck and D. Fox · 2016
Earlier work this paper cites.
Least-Squares Rigid Motion Using SVD
O. Sorkine-Hornung and M. Rabinovich · 2016
Earlier work this paper cites.
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
C. R. Qi, H. Su, K. Mo, and L. J. Guibas · 2017
Earlier work this paper cites.
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
C. R. Qi, L. Yi, H. Su, and L. J. Guibas · 2017
Earlier work this paper cites.
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
Y. Zhou and O. Tuzel · 2017
Earlier work this paper cites.
Learning Robotic Manipulation of Granular Media
C. Schenck, J. Tompson, D. Fox, and S. Levine · 2017
Earlier work this paper cites.
Visual Closed-Loop Control for Pouring Liquids
C. Schenck and D. Fox · 2017
Earlier work this paper cites.
Soft Actor-Critic Algorithms and Applications
T. Haarnoja, A. Zhou, K. Hartikainen, G. Tucker, S. Ha, J. Tan, V. Kumar, H. Zhu, A. Gupta, P. Abbeel, and S. Levine · 2018
Earlier work this paper cites.
Robotic Manipulation and Sensing of Deformable Objects in Domestic and Industrial Applications: a Survey
J. Sanchez, J.-A. Corrales, B.-C. Bouzgarrou, and Y. Mezouar · 2018
Earlier work this paper cites.
SPNets: Differentiable Fluid Dynamics for Deep Neural Networks
C. Schenck and D. Fox · 2018
Earlier work this paper cites.
Learning Audio Feedback for Estimating Amount and Flow of Granular Material
S. Clarke, T. Rhodes, C. G. Atkeson, and O. Kroemer · 2018
Earlier work this paper cites.
An Algorithmic Perspective on Imitation Learning
T. Osa, J. Pajarinen, G. Neumann, J. A. Bagnell, P. Abbeel, and J. Peters · 2018
Earlier work this paper cites.
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
Y. Xiang, T. Schmidt, V. Narayanan, and D. Fox · 2018
Cited alongside, same era.
DeepIM: Deep Iterative Matching for 6D Pose Estimation
Y. Li, G. Wang, X. Ji, Y. Xiang, and D. Fox · 2018
Cited alongside, same era.
Deep Reinforcement Learning that Matters
P. Henderson, R. Islam, P. Bachman, J. Pineau, D. Precup, and D. Meger · 2018
Cited alongside, same era.
Deep Q-learning from Demonstrations
T. Hester, M. Vecerik, O. Pietquin, M. Lanctot, T. Schaul, B. Piot, D. Horgan, J. Quan, A. Sendonaris, G. Dulac-Arnold, I. Osband, J. Agapiou, J. Z. Leibo, and A. Gruslys · 2018
Cited alongside, same era.
Overcoming Exploration in Reinforcement Learning with Demonstrations
A. Nair, B. McGrew, M. Andrychowicz, W. Zaremba, and P. Abbeel · 2018
Cited alongside, same era.
Learning Ambidextrous Robot Grasping Policies
J. Mahler, M. Matl, V. Satish, M. Danielczuk, B. DeRose, S. McKinley, and K. Goldberg · 2019
A Smooth Representation of Belief over SO(3) for Deep Rotation Learning with Uncertainty
V. Peretroukhin, M. Giamou, D. M. Rosen, W. N. Greene, N. Roy, and J. Kelly · 2020
Later among the works it cites.
CURL: Contrastive Unsupervised Representations for Reinforcement Learning
A. Srinivas, M. Laskin, and P. Abbeel · 2020
Later among the works it cites.
Accelerating 3D Deep Learning with PyTorch3D
N. Ravi, J. Reizenstein, D. Novotny, T. Gordon, W.-Y. Lo, J. Johnson, and G. Gkioxari · 2020
Later among the works it cites.
Toward Orientation Learning and Adaptation in Cartesian Space
Y. Huang, F. J. Abu-Dakka, J. Silverio, and D. G. Caldwell · 2020
Later among the works it cites.
Challenges and Outlook in Robotic Manipulation of Deformable Objects
J. Zhu, A. Cherubini, C. Dune, D. Navarro-Alarcon, F. Alambeigi, D. Berenson, F. Ficuciello, K. Harada, J. Kober, X. Li, J. Pan, W. Yuan, and M. Gienger · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Learning Dexterous In-Hand Manipulation
OpenAI, M. Andrychowicz, B. Baker, M. Chociej, R. Jozefowicz, B. McGrew, J. Pachocki, A. Petron, M. Plappert, G. Powell, A. Ray, J. Schneider, S. Sidor, J. Tobin, P. Welinder, L. Weng, and W. Zaremba · 2019
Cited alongside, same era.
TossingBot: Learning to Throw Arbitrary Objects with Residual Physics
A. Zeng, S. Song, J. Lee, A. Rodriguez, and T. Funkhouser · 2019
Cited alongside, same era.
Solving Rubik’s Cube with a Robot Hand
OpenAI, I. Akkaya, M. Andrychowicz, M. Chociej, M. Litwin, B. McGrew, A. Petron, A. Paino, M. Plappert, G. Powell, R. Ribas, J. Schneider, N. Tezak, J. Tworek, P. Welinder, L. Weng, Q. Yuan, W. Zaremba, and L. Zhang · 2019
Cited alongside, same era.
A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms
O. Kroemer, S. Niekum, and G. Konidaris · 2019
Cited alongside, same era.
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
Cited alongside, same era.
Point-Voxel CNN for Efficient 3D Deep Learning
Z. Liu, H. Tang, Y. Lin, and S. Han · 2019
Cited alongside, same era.
Later among the works it cites.
PointTransformer
H. Zhao, L. Jiang, J. Jia, P. Torr, and V. Koltun · 2021
Later among the works it cites.
A System for General In-Hand Object Re-Orientation
T. Chen, J. Xu, and P. Agrawal · 2021
Later among the works it cites.
Goal-Auxiliary Actor-Critic for 6D Robotic Grasping with Point Clouds
L. Wang, Y. Xiang, W. Yang, A. Mousavian, and D. Fox · 2021
Later among the works it cites.
RAFT-3D: Scene Flow using Rigid-Motion Embeddings
Z. Teed and J. Deng · 2021
Later among the works it cites.
FabricFlowNet: Bimanual Cloth Manipulation with a Flow-based Policy
T. Weng, S. Bajracharya, Y. Wang, K. Agrawal, and D. Held · 2021
Later among the works it cites.
Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry
S. Dong, D. K. Jha, D. Romeres, S. Kim, D. Nikovski, and A. Rodriguez · 2021
Later among the works it cites.
RB2: Robotic Manipulation Benchmarking with a Twist
S. Dasari, J. Wang, J. Hong, S. Bahl, Y. Lin, A. Wang, A. Thankaraj, K. Chahal, B. Calli, S. Gupta, D. Held, L. Pinto, D. Pathak, V. Kumar, and A. Gupta · 2021
Later among the works it cites.
Implicit Behavioral Cloning
P. Florence, C. Lynch, A. Zeng, O. Ramirez, A. Wahid, L. Downs, A. Wong, J. Lee, I. Mordatch, and J. Tompson · 2021
Later among the works it cites.
Coarse-to-Fine Imitation Learning: Robot Manipulation from a Single Demonstration
E. Johns · 2021
Later among the works it cites.
Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks
D. Seita, P. Florence, J. Tompson, E. Coumans, V. Sindhwani, K. Goldberg, and A. Zeng · 2021
Later among the works it cites.
Orientation Probabilistic Movement Primitives on Riemannian Manifolds
L. Rozo and V. Dave · 2021
Later among the works it cites.
Learning Stable Vector Fields on Lie Groups
J. Urain, D. Tateo, and J. Peters · 2021
Later among the works it cites.
Learning Generalizable Dexterous Manipulation from Human Grasp Affordance
Y.-H. Wu, J. Wang, and X. Wang · 2022
Closest in time.
Learning Visual Shape Control of Novel 3D Deformable Objects from Partial-View Point Clouds
B. Thach, B. Y. Cho, A. Kuntz, and T. Hermans · 2022
Closest in time.
FlowBot3D: Learning 3D Articulation Flow to Manipulate Articulated Objects
B. Eisner, H. Zhang, and D. Held · 2022
Closest in time.
ACID: Action-Conditional Implicit Visual Dynamics for Deformable Object Manipulation
B. Shen, Z. Jiang, C. Choy, L. J. Guibas, S. Savarese, A. Anandkumar, and Y. Zhu · 2022
Closest in time.
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
Closest in time.
Learning Deformable Object Manipulation from Expert Demonstrations
G. Salhotra, I.-C. A. Liu, M. Dominguez-Kuhne, and G. S. Sukhatme · 2022
Closest in time.
Projective Manifold Gradient Layer for Deep Rotation Regression
J. Chen, Y. Yin, T. Birdal, B. Chen, L. Guibas, and H. Wang · 2022
Closest in time.
Frame Mining: a Free Lunch for Learning Robotic Manipulation from 3D Point Clouds
M. Liu, X. Li, Z. Ling, Y. Li, and H. Su · 2022
Closest in time.