A curated list of papers about point cloud registration inspired by awesome point cloud analysis
You will be very welcome to make PR and contribute!! ๐
lf.
: local features for registration โ | โ
corr.
: register with putative correspondences โ | โ
est.
: direct estimation โ | โ
dat.
: datasets โ | โ
opt.
: optimization โ | โ
oth.
: other
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[CGF] Sparse Iterative Closest Point. [code] [
est.
opt.
] ๐ฅ โญ -
[IJRR] Challenging data sets for point cloud registration algorithms. [code] [
dat.
] โญ
-
[CVPR] 3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions. [code] [
lf.
dat.
] ๐ฅ โญ -
[CVPR] 3D Point Cloud Registration for Localization using a Deep Neural Network Auto-Encoder. [code] [
est.
] -
[ICCV] Learning Compact Geometric Features. [code] [
est.
dat.
]
-
[ECCV] 3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration [code] [
lf.
] -
[ECCV] PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors [
lf.
] -
[CVPR] PPFNet: Global Context Aware Local Features for Robust 3D Point Matching [
lf.
] -
[CVPR] End-to-end learning of keypoint detector and descriptor for pose invariant 3D matching [
lf.
] -
[CVPR] Inverse Composition Discriminative Optimization for Point Cloud Registration [
opt.
]
-
[CVPR] PointNetLK: Robust & Efficient Point Cloud Registration using PointNet. [code] [
est.
] ๐ฅ -
[CVPR] DeepMapping: Unsupervised Map Estimation From Multiple Point Clouds. [code] [
est.
opt.
] ๐ฅ -
[CVPR] The Perfect Match: 3D Point Cloud Matching with Smoothed Densities [code] [
lf.
] -
[CVPR] L3 -Net: Towards Learning based LiDAR Localization for Autonomous Driving [
lf.
est.
] -
[CVPR] SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences [code] [
est.
opt.
] -
[CVPR] 3D Local Features for Direct Pairwise Registration [
lf.
est.
] -
[CVPR] GFrames: Gradient-Based Local Reference Frame for 3D Shape Matching [
oth.
] -
[CVPR] FilterReg: Robust and Efficient Probabilistic Point-Set Registration using Gaussian Filter and Twist Parameterization [code] [
opt.
oth.
] -
[ICCV] DeepVCP: An End-to-End Deep Neural Network for Point Cloud Registration [
est.
lf.
] -
[ICCV] Deep Closest Point: Learning Representations for Point Cloud Registration [code] [
est.
] -
[ICCV] USIP: Unsupervised Stable Interest Point Detection from 3D Point Clouds. [code] [
lf.
] -
[ICCV] Learning an Effective Equivariant 3D Descriptor Without Supervision. [
lf.
] -
[ICRA] Robust low-overlap 3-D point cloud registration for outlier rejection [
est.
opt.
corr.
oth.
] -
[ICRA] CELLO-3D: Estimating the Covariance of ICP in the Real World [
est.
opt.
oth.
] -
[NeurIPS] PRNet: Self-Supervised Learning for Partial-to-Partial Registration [
est.
] -
[TOG] A Symmetric Objective Function for ICP [
est.
opt.
] -
[ARXIV] 3DRegNet: A Deep Neural Network for 3D Point Registration [
est.
] -
[ARXIV] Iterative Matching Point [
est.
] -
[ARXIV] PCRNet: Point Cloud Registration Network using PointNet Encoding [code] [
est.
]
- [CVPR] End-to-End Learning Local Multi-view Descriptors for 3D Point Clouds [code] [
lf.
] - [CVPR] D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features [code] [
lf.
] - [CVPR] 3DRegNet: A Deep Neural Network for 3D Point Registration [code] [
corr.
] - [CVPR] High-Dimensional Convolutional Networks for Geometric Pattern Recognition [code] [
corr.
] - [CVPR] Deep Global Registration [code] [
lf.
corr.
] - [CVPR] Learning multiview 3D point cloud registration [code] [
corr.
oth.
] - [CVPR] RPM-Net: Robust Point Matching using Learned Features [code] [
est.
] - [CVPR] Feature-metric Registration: A Fast Semi-supervised Approach for Robust Point Cloud Registration without Correspondences [code] [
opt.
est.
oth.
] - [CVPR] PointGMM: a Neural GMM Network for Point Clouds [
est.
oth.
] - [ECCV] DeepGMR: Learning Latent Gaussian Mixture Models for Registration [code] [
est.
corr.
]