(no subject)
Some links on DNNs and CNNs for
motion synthesis (also LSTM, etc).
There are also some on visuo-motor
features learning.
Not included: the old NNs papers as
[Faloutsos, Van De Panne, Terzopoulos, 2001],
[Grzeszczuk, Terzopoulos, Hinton, 1998],
[Shao, Terzopoulos, 2005], [Terzopoulos, 2009],
[Rose III, Sloan, Cohen, 2001], etc.
S.Levine, C.Finn, T.Darrell, P.Abbeel (2016)
"End-to-End Training of Deep Visuomotor Policies."
A.Tamar, Y.Wu, G.Thomas, S.Levine, P.Abbeel (2016)
"Value Iteration Networks" Adv. NIPS 29 (NIPS'16).
C.Finn, P.Abbeel, S.Levine (2017)
"Model-Agnostic Meta-Learning for
Fast Adaptation of Deep Networks."
C.Finn, X.Y.Tan, Y.Duan, T.Darrell,
S.Levine, P.Abbeel (2015) "Learning
Visual Feature Spaces for Robotic
Manipulation with Deep Spatial
Autoencoders." (And here.)
M.Watter, J.Springenberg, J.Boedecker,
M.Riedmiller (2015) "Embed to Control:
A Locally Linear Latent Dynamics Model
for Control from Raw Images."
Adv. NIPS 28 (NIPS'15).
Holden, D., Saito, J., Komura, T., (2016)
"A Deep Learning Framework for Character Motion
Synthesis and Editing" Siggraph’16 Techn. Paper.
Holden, D., Saito, J., Komura, T., Joyce, T. (2015)
"Learning motion manifolds with convolutional autoencoders"
In SIGGRAPH Asia 2015 Techn. Briefs, ACM, 18:1-18:4.
Levine, S., Koltun, V. (2014)
"Learning complex neural network
policies with trajectory optimization"
In Proc. of the 31st Int. Conf.
on M.L. (ICML-14), 829-837.
Du, Y., Wang, W., Wang, L. (2015)
"Hierarchical recurrent neural network
for skeleton based action recognition"
In Proc. of the IEEE Conf. on
Computer Vision and Pattern Rec.
Taylor, G.W., Hinton, G.E., Roweis , S.T. (2011)
"Two distributed-state models for generating
high-dimensional time series" The J. of
Machine Learn. Res. 12, 1025-1068.
Mittelman, R., Kuipers, B., Savarese, S., Lee, H. (2014)
"Structured recurrent temporal restricted Boltzmann Machines"
In Proc. of the 31st Int. Conf. on M.L. (ICML-14), 1647-1655.
Fragkiadaki, K., Levine, S., Felsen, P., Malik, J. (2015)
"Recurrent network models for human dynamics." In Proc.
of the IEEE Int. Conf. on Comp. Vis., 4346-4354. ArXiv.
C.Donahue, Z.C.Lipton, J.McAuley (2017)
"Dance Dance Convolution." ArXiv.
A.Byravan, D.Fox (2017)
"SE3-Nets: Learning Rigid Body
Motion using Deep Neural Networks."
L.Deng, G.Hinton, B.Kingsbury (2013)
"New types of deep neural network learning
for speech recognition and related applications:
An overview." ICASSP, 2013. IEEE.
E.Johns, S.Leutenegger, A.J.Davison (2016)
"Deep learning a grasp function for grasping
under gripper pose uncertainty." ArXiv.
Some can be found also here.
motion synthesis (also LSTM, etc).
There are also some on visuo-motor
features learning.
Not included: the old NNs papers as
[Faloutsos, Van De Panne, Terzopoulos, 2001],
[Grzeszczuk, Terzopoulos, Hinton, 1998],
[Shao, Terzopoulos, 2005], [Terzopoulos, 2009],
[Rose III, Sloan, Cohen, 2001], etc.
S.Levine, C.Finn, T.Darrell, P.Abbeel (2016)
"End-to-End Training of Deep Visuomotor Policies."
A.Tamar, Y.Wu, G.Thomas, S.Levine, P.Abbeel (2016)
"Value Iteration Networks" Adv. NIPS 29 (NIPS'16).
C.Finn, P.Abbeel, S.Levine (2017)
"Model-Agnostic Meta-Learning for
Fast Adaptation of Deep Networks."
C.Finn, X.Y.Tan, Y.Duan, T.Darrell,
S.Levine, P.Abbeel (2015) "Learning
Visual Feature Spaces for Robotic
Manipulation with Deep Spatial
Autoencoders." (And here.)
M.Watter, J.Springenberg, J.Boedecker,
M.Riedmiller (2015) "Embed to Control:
A Locally Linear Latent Dynamics Model
for Control from Raw Images."
Adv. NIPS 28 (NIPS'15).
Holden, D., Saito, J., Komura, T., (2016)
"A Deep Learning Framework for Character Motion
Synthesis and Editing" Siggraph’16 Techn. Paper.
Holden, D., Saito, J., Komura, T., Joyce, T. (2015)
"Learning motion manifolds with convolutional autoencoders"
In SIGGRAPH Asia 2015 Techn. Briefs, ACM, 18:1-18:4.
Levine, S., Koltun, V. (2014)
"Learning complex neural network
policies with trajectory optimization"
In Proc. of the 31st Int. Conf.
on M.L. (ICML-14), 829-837.
Du, Y., Wang, W., Wang, L. (2015)
"Hierarchical recurrent neural network
for skeleton based action recognition"
In Proc. of the IEEE Conf. on
Computer Vision and Pattern Rec.
Taylor, G.W., Hinton, G.E., Roweis , S.T. (2011)
"Two distributed-state models for generating
high-dimensional time series" The J. of
Machine Learn. Res. 12, 1025-1068.
Mittelman, R., Kuipers, B., Savarese, S., Lee, H. (2014)
"Structured recurrent temporal restricted Boltzmann Machines"
In Proc. of the 31st Int. Conf. on M.L. (ICML-14), 1647-1655.
Fragkiadaki, K., Levine, S., Felsen, P., Malik, J. (2015)
"Recurrent network models for human dynamics." In Proc.
of the IEEE Int. Conf. on Comp. Vis., 4346-4354. ArXiv.
C.Donahue, Z.C.Lipton, J.McAuley (2017)
"Dance Dance Convolution." ArXiv.
A.Byravan, D.Fox (2017)
"SE3-Nets: Learning Rigid Body
Motion using Deep Neural Networks."
L.Deng, G.Hinton, B.Kingsbury (2013)
"New types of deep neural network learning
for speech recognition and related applications:
An overview." ICASSP, 2013. IEEE.
E.Johns, S.Leutenegger, A.J.Davison (2016)
"Deep learning a grasp function for grasping
under gripper pose uncertainty." ArXiv.
Some can be found also here.