Papers with Code 아카이브
3D Point Cloud Interpolation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 2
- 보존된 평가 기록
- 9
Point cloud interpolation is a fundamental problem for 3D computer vision. Given a low temporal resolution (frame rate) point cloud sequence, the target of interpolation is to generate a smooth point cloud sequence with high temporal resolution (frame rate).
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
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
https://github.com/jewettaij/superpose3d
https://github.com/jiang-hb/diffusionreg
SE(3) Diffusion Model-based Point Cloud Registration for Robust 6D Object Pose Estimation
https://github.com/jimmy15923/unsup_point_coseg
https://github.com/julians89/PointNetLK-Tensorflow
PointNetLK: Robust & Efficient Point Cloud Registration using PointNet
https://github.com/kylevedder/SparsePointPillars
https://github.com/liangp/mcstn-3dsot
Model-free Vehicle Tracking and State Estimation in Point Cloud Sequences
https://github.com/liuQuan98/GCL-KPConv
Density-invariant Features for Distant Point Cloud Registration
https://github.com/lucifer443/SpineNet-Pytorch
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
https://github.com/luckyluckydadada/lucky-Open3D-ML-0.13
https://github.com/marckhoury/CGF
https://github.com/mergarsal/FastCertRelPose
https://github.com/overlappredator/OverlapPredator
https://github.com/paul007pl/VRCNet
https://github.com/prs-eth/overlappredator
https://github.com/pwc-1/Paper-9/tree/main/6/LIE-IQA
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras
https://github.com/rajahaseeb147/PCD_Registration_ReAgent
ReAgent: Point Cloud Registration using Imitation and Reinforcement Learning
https://github.com/securade/hub
A Maximum Likelihood Approach to Extract Finite Planes from 3-D Laser Scans
https://github.com/sumo-agarwal/open3d
https://github.com/tensorflow/tpu/tree/master/models/official/detection
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
https://github.com/uncbiag/robot
Accurate Point Cloud Registration with Robust Optimal Transport
https://github.com/vinits5/PointNetLK
PointNetLK: Robust & Efficient Point Cloud Registration using PointNet
https://github.com/weitong8591/ars_magsac
https://github.com/wzh99/DCP-TF
Deep Closest Point: Learning Representations for Point Cloud Registration
https://github.com/yan-roo/SpineNet-Pytorch
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
https://github.com/yikakabu/PPF-FoldNet
PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors
https://github.com/zhulf0804/predator
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.