Visual Results by Method

Results for methods appear here after users upload them and approve them for public display.





Metrics


Average error
Error visualization: for each pair, the plot on the left reports the errors in cm for all the ground-truth correspondences (sorted by decreasing error).

For the intra-subject challenge, the figure on the right shows the error distribution over the vertices of the first scan in the pair (blue represents the minimum error, red represents the maximum error).

For the inter-subject challenge, the figure on the right shows the error distribution over different areas of the first scan in the pair (each area corresponds to a landmark location; black represents the minimum error, white represents the maximum error).


References
[1]
JOMS-inter-combined
Anonymous.
[2]
JOMS-inter-unisex
Anonymous.
[3]
2icp
[4]
3D-CODED : 3D Correspondences by Deep Deformation
3D-CODED : 3D Correspondences by Deep Deformation, Groueix, Thibault and Fisher, Matthew and Kim, Vladimir G. and Russell, Bryan and Aubry, Mathieu, ECCV 2018.
[5]
BPS
Efficient Learning on Point Clouds with Basis Point Sets
[6]
CHARM
[7]
combine-test
[8]
Convex-Opt
Robust Nonrigid Registration by Convex Optimization. Qifeng Chen, Vladlen Koltun. International Conference on Computer Vision (ICCV), 2015
[9]
DHNN_ours_e1
Disentangled Human Body Embedding Based on Deep Hierarchical Neural Network. IEEE TVCG 2020
[10]
DHNN_ours_e2
Disentangled Human Body Embedding Based on Deep Hierarchical Neural Network. IEEE TVCG 2020
[11]
DHNN_ours1
Disentangled Human Body Embedding Based on Deep Hierarchical Neural Network. IEEE TVCG 2020
[12]
DHNN_ours2
Disentangled Human Body Embedding Based on Deep Hierarchical Neural Network. IEEE TVCG 2020
[13]
FARM
"FARM: Functional Automatic Registration Method for 3D Human Bodies". Marin, Melzi, Rodola, Castellani. arXiv:1807.10517, 2018.
[14]
fixed mesh
Use unsurpervised loss. 0, true, 0 fixed meshes
[15]
FMNet
"Deep functional maps: Structured prediction for dense shape correspondence". Litany, Remez, Rodola, Bronstein, Bronstein. Proc. ICCV 2017
[16]
george intra
[17]
george_test_folder
Anonymous.
[18]
george_test_folder
Anonymous.
[19]
george_test_folder
Anonymous.
[20]
george_test_folder
Anonymous.
[21]
george_test_folder
Anonymous.
[22]
george_test_folder
Anonymous.
[23]
Inter Test FT2 LR Fr
Anonymous.
[24]
Inter Test FT2 LR Fr
Anonymous.
[25]
Intra Test Fr
Anonymous.
[26]
Intra Test Fr
Anonymous.
[27]
Intra Test Fr
Anonymous.
[28]
Intra Test FT2 LR Fr
Anonymous.
[29]
JOMS-inter-female
Anonymous.
[30]
JOMS-inter-male
Anonymous.
[31]
JOMS-intra-combined
Anonymous.
[32]
JOMS-intra-female
Anonymous.
[33]
JOMS-intra-male
Anonymous.
[34]
JOMS-intra-unisex
Anonymous.
[35]
LBS-AE (Unsupervised)
LBS Autoencoder: Self-supervised Fitting of Articulated Meshes to Point Clouds, CVPR 2019
[36]
Learning elementary structures for 3D shape generation and matching
Learning elementary structures for 3D shape generation and matching, Deprelle, Theo, Groueix, Thibault and Fisher, Matthew and Kim, Vladimir G. and Russell, Bryan and Aubry, Mathieu, ECCV 2018
[37]
PAI_GCN
TBD TBD
[38]
Reproduce FMNet
[39]
reproduce UFMNet
[40]
reproduce UFMNet 1
with 10, true, 10 Oshri data
[41]
reproduce UFMNet 2
20, true, 20 Oshri data
[42]
SP_intra_challenge
S. Zuffi, M. J. Black, "The Stitched Puppet: A Graphical Model of 3D Human Shape and Pose", CVPR, Boston, MA, June 2015.
[43]
test-2icp-2refine
[44]
unsupervised 3D-CODED : 3D Correspondences by Deep Deformation
3D-CODED : 3D Correspondences by Deep Deformation, Groueix, Thibault and Fisher, Matthew and Kim, Vladimir G. and Russell, Bryan and Aubry, Mathieu, ECCV 2018.
[45]
Unsupervised Cyclic mapper intra
Cyclic Functional Mapping: Self-supervised correspondence between non-isometric deformable shapes
[46]
Unsupervised Learning of Dense Shape Correspondence
Unsupervised Learning of Dense Shape Correspondence, Oshri Halimi, Or Litany, Emanuele Rodola, Alex M. Bronstein, Ron Kimmel; (CVPR 2019)
[47]
Unsupervised Learning of Dense Shape Correspondence
Unsupervised Learning of Dense Shape Correspondence, Oshri Halimi, Or Litany, Emanuele Rodola, Alex M. Bronstein, Ron Kimmel; (CVPR 2019)