https://github.com/MStypulkowski/CIF
Representing Point Clouds with Generative Conditional Invertible Flow Networks
Papers with Code 아카이브
Point Cloud Registration
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 24
- 보존된 평가 기록
- 190
Point Cloud Registration is a fundamental problem in 3D computer vision and photogrammetry. Given several sets of points in different coordinate systems, the aim of registration is to find the transformation that best aligns all of them into a common coordinate system. Point Cloud Registration plays a significant role in many vision applications such as 3D model reconstruction, cultural heritage management, landslide monitoring and solar energy analysis.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MindCode-4/code-14/tree/main/LIE-IQA
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras
https://github.com/MindSpore-paper-code-2/code3/tree/main/ssd_resnet_34
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
https://github.com/NomitRwt/DiplomaProject
https://github.com/Pacific-cyber/KUKA_Catch_Project
SegICP: Integrated Deep Semantic Segmentation and Pose Estimation
https://github.com/STORM-IRIT/OpenGR
https://github.com/StrikerCC/Teaser-plusplus-testing
https://github.com/XuyangBai/D3Feat.pytorch
D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features
https://github.com/XuyangBai/PPF-FoldNet
PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors
https://github.com/bigeyesung/test1
https://github.com/changliu816/CV-paper-review
https://github.com/chrischoy/FCGF
https://github.com/code-implementation1/Code7/tree/main/retinanet_resnet101
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
https://github.com/code-implementation1/Code8/tree/main/SpineNet
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
https://github.com/code-implementation1/Code9/tree/main/PVNet
PointNetLK: Robust & Efficient Point Cloud Registration using PointNet
https://github.com/code-implementation1/Code9/tree/main/PointNet
PointNetLK: Robust & Efficient Point Cloud Registration using PointNet
https://github.com/contiliosung/open3D
https://github.com/craigleili/3DLocalMultiViewDesc
End-to-End Learning Local Multi-view Descriptors for 3D Point Clouds
https://github.com/dahliau/DPDist
PCRNet: Point Cloud Registration Network using PointNet Encoding
https://github.com/dengzhi-ustc/a-robust-registration-loss
3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions
https://github.com/edikkesh/Open3D
https://github.com/esteimle/teaser
https://github.com/fpthink/stnet
Model-free Vehicle Tracking and State Estimation in Point Cloud Sequences
https://github.com/fpthink/v2b
Model-free Vehicle Tracking and State Estimation in Point Cloud Sequences
https://github.com/ftdlyc/KCNet_Pytorch
Mining Point Cloud Local Structures by Kernel Correlation and Graph Pooling
https://github.com/grossjohannes/AlignNet-3D
AlignNet-3D: Fast Point Cloud Registration of Partially Observed Objects
https://github.com/haoyu94/roitr
RIGA: Rotation-Invariant and Globally-Aware Descriptors for Point Cloud Registration
https://github.com/hkust-aerial-robotics/g3reg
Pyramid Semantic Graph-based Global Point Cloud Registration with Low Overlap
https://github.com/hui-design/aand
PARE-Net: Position-Aware Rotation-Equivariant Networks for Robust Point Cloud Registration
https://github.com/intel-isl/Open3D
https://github.com/intel-isl/Open3D-ML
https://github.com/isl-org/FastGlobalRegistration
https://github.com/isl-org/Open3D
https://github.com/isl-org/Open3D-ML
https://github.com/isl-org/Open3D/blob/main/cpp/open3d/pipelines/registration/Feature.h
https://github.com/izhangrui/paper_to_read
PointNetLK: Robust & Efficient Point Cloud Registration using PointNet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.