Fetching the paper…
Reading the bibliography…
We present a novel deep neural network architecture for end-to-end scene flow estimation that directly operates on large-scale 3D point clouds.
Method for registration of 3-d shapes
P.J. Besl and N.D. McKay · 1992
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.
High accuracy optical flow estimation based on a theory for warping
T. Brox, A. Bruhn, N. Papenberg, and J. Weickert · 2004
Earlier work this paper cites.
Some useful properties of the permutohedral lattice for gaussian filtering
J. Baek and A.B. Adams · 2009
Earlier work this paper cites.
Fast high-dimensional filtering using the permutohedral lattice
A. Adams, J. Baek, and M.A. Davis · 2010
Earlier work this paper cites.
High-dimensional gaussian filtering for computational photography
A.B. Adams · 2011
Earlier work this paper cites.
Rgb-d flow: Dense 3-d motion estimation using color and depth
E. Herbst, X. Ren, and D. Fox · 2013
Earlier work this paper cites.
Spectral networks and locally connected networks on graphs
J. Bruna, W. Zaremba, A. Szlam, and Y. LeCun · 2014
Earlier work this paper cites.
Learning class-specific descriptors for deformable shapes using localized spectral convolutional networks
D. Boscaini, J. Masci, S. Melzi, M.M. Bronstein, U. Castellani, and P. Vandergheynst · 2015
Earlier work this paper cites.
Flownet: Learning optical flow with convolutional networks
A. Dosovitskiy, P. Fischer, E. Ilg, P. Hausser, C. Hazirbas, V. Golkov, P. Van Der Smagt, D. Cremers, and T. Brox · 2015
Earlier work this paper cites.
Deep convolutional networks on graph-structured data
M. Henaff, J. Bruna, and Y. LeCun · 2015
Earlier work this paper cites.
Permutohedral lattice cnns
M. Kiefel, V. Jampani, and P.V. Gehler · 2015
Earlier work this paper cites.
Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
Earlier work this paper cites.
Voxnet: A 3d convolutional neural network for real-time object recognition
D. Maturana and S. Scherer · 2015
Earlier work this paper cites.
Object scene flow for autonomous vehicles
M. Menze and A. Geiger · 2015
Earlier work this paper cites.
Joint 3d estimation of vehicles and scene flow
M. Menze, C. Heipke, and A. Geiger · 2015
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
O. Ronneberger, P. Fischer, and T. Brox · 2015
Cited alongside, same era.
Multi-view convolutional neural networks for 3d shape recognition
H. Su, S. Maji, E. Kalogerakis, and E. Learned-Miller · 2015
Cited alongside, same era.
3d shapenets: A deep representation for volumetric shapes
Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, and J. Xiao · 2015
Cited alongside, same era.
Gift: A real-time and scalable 3d shape search engine
S. Bai, X. Bai, Z. Zhou, Z. Zhang, and L. Jan Latecki · 2016
Cited alongside, same era.
Convolutional neural networks on graphs with fast localized spectral filtering
M. Defferrard, X. Bresson, and P. Vandergheynst · 2016
Cited alongside, same era.
Rigid scene flow for 3d lidar scans
A. Dewan, T. Caselitz, G.D. Tipaldi, and W. Burgard · 2016
Cited alongside, same era.
3d shape segmentation with projective convolutional networks
E. Kalogerakis, M. Averkiou, S. Maji, and S. Chaudhuri · 2017
Later among the works it cites.
Escape from cells: Deep kd-networks for the recognition of 3d point cloud models
R. Klokov and V. Lempitsky · 2017
Later among the works it cites.
Pointnet: Deep learning on point sets for 3d classification and segmentation
C.R. Qi, H. Su, K. Mo, and L.J. Guibas · 2017
Later among the works it 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
Later among the works it cites.
Optical flow estimation using a spatial pyramid network
A. Ranjan and M.J. Black · 2017
Later among the works it cites.
A learning approach for real-time temporal scene flow estimation from lidar data
A.K. Ushani, R.W. Wolcott, J.M. Walls, and R.M. Eustice · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Learning sparse high dimensional filters: Image filtering, dense crfs and bilateral neural networks
V. Jampani, M. Kiefel, and P.V. Gehler · 2016
Cited alongside, same era.
A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation
N. Mayer, E. Ilg, P. Hausser, P. Fischer, D. Cremers, A. Dosovitskiy, and T. Brox · 2016
Cited alongside, same era.
Volumetric and multi-view cnns for object classification on 3d data
C.R. Qi, H. Su, M. Nießner, A. Dai, M. Yan, and L.J. Guibas · 2016
Cited alongside, same era.
Scene flow estimation: A survey
Z. Yan and X. Xiang · 2016
Cited alongside, same era.
Stereo matching by training a convolutional neural network to compare image patches
J. Zbontar and Y. LeCun · 2016
Cited alongside, same era.
3d object classification via spherical projections
Z. Cao, Q. Huang, and R. Karthik · 2017
Cited alongside, same era.
Later among the works it cites.
Syncspeccnn: Synchronized spectral cnn for 3d shape segmentation
L. Yi, H. Su, X. Guo, and L.J. Guibas · 2017
Later among the works it cites.
3d semantic segmentation with submanifold sparse convolutional networks
B. Graham, M. Engelcke, and L. van der Maaten · 2018
Later among the works it cites.
Occlusions, motion and depth boundaries with a generic network for disparity, optical flow or scene flow estimation
E. Ilg, T. Saikia, M. Keuper, and T. Brox · 2018
Later among the works it cites.
Learning scene flow in 3d point clouds
X. Liu, C.R. Qi, and L.J. Guibas · 2018
Later among the works it cites.
3d scene flow from 4d light field gradients
S. Ma, B.M. Smith, and M. Gupta · 2018
Later among the works it cites.
Object scene flow
M. Menze, C. Heipke, and A. Geiger · 2018
Later among the works it cites.
Splatnet: Sparse lattice networks for point cloud processing
H. Su, V. Jampani, D. Sun, S. Maji, E. Kalogerakis, M.H. Yang, and J. Kautz · 2018
Later among the works it cites.
A closer look at spatiotemporal convolutions for action recognition
D. Tran, H. Wang, L. Torresani, J. Ray, Y. LeCun, and M. Paluri · 2018
Later among the works it cites.
Deep parametric continuous convolutional neural networks
S. Wang, S. Suo, W.C. Ma, A. Pokrovsky, and R. Urtasun · 2018
Later among the works it cites.