https://github.com/ai4ce/DeepMapping2
공식 코드DeepMapping2: Self-Supervised Large-Scale LiDAR Map Optimization
Papers with Code 아카이브
Point Cloud Registration
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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/aibluefisher/dreg-nerf
공식 코드https://github.com/alexandor91/se3-equi-graph-registration
공식 코드Equi-GSPR: Equivariant SE(3) Graph Network Model for Sparse Point Cloud Registration
https://github.com/aliyoussef97/silk-prp
공식 코드https://github.com/amnondrory/lidarregistration
공식 코드https://github.com/amyyyy11/3d-registration-in-30-years-a-survey
공식 코드https://github.com/andyzeng/3dmatch-toolbox
공식 코드3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions
https://github.com/aralab-unr/esm_icp
공식 코드Registration of 3D Point Sets Using Exponential-based Similarity Matrix
https://github.com/ariarobotics/clipperp
공식 코드CLIPPER+: A Fast Maximal Clique Algorithm for Robust Global Registration
https://github.com/arpg/bo_icp
공식 코드BO-ICP: Initialization of Iterative Closest Point Based on Bayesian Optimization
https://github.com/axeber01/point-tnt
공식 코드Points to Patches: Enabling the Use of Self-Attention for 3D Shape Recognition
https://github.com/boschresearch/direg
공식 코드Unsupervised Point Cloud Registration with Self-Distillation
https://github.com/cguangyan-bit/dit
공식 코드Full Transformer Framework for Robust Point Cloud Registration with Deep Information Interaction
https://github.com/chen-suyi/pointreggpt
공식 코드PointRegGPT: Boosting 3D Point Cloud Registration using Generative Point-Cloud Pairs for Training
https://github.com/chirikjianlab/lsg-cpd
공식 코드LSG-CPD: Coherent Point Drift with Local Surface Geometry for Point Cloud Registration
https://github.com/chrischoy/DeepGlobalRegistration
공식 코드https://github.com/craigleili/wsdesc
공식 코드WSDesc: Weakly Supervised 3D Local Descriptor Learning for Point Cloud Registration
https://github.com/csiro-robotics/spectralgv
공식 코드Spectral Geometric Verification: Re-Ranking Point Cloud Retrieval for Metric Localization
https://github.com/davidboja/greedy-grid-search
공식 코드Challenging the Universal Representation of Deep Models for 3D Point Cloud Registration
https://github.com/dfki-av/sg-pgm
공식 코드https://github.com/dornik/reagent
공식 코드ReAgent: Point Cloud Registration using Imitation and Reinforcement Learning
https://github.com/ericssonresearch/colabsfm
공식 코드ColabSfM: Collaborative Structure-from-Motion by Point Cloud Registration
https://github.com/fabiopoiesi/dip
공식 코드https://github.com/fabiopoiesi/gedi
공식 코드Learning general and distinctive 3D local deep descriptors for point cloud registration
https://github.com/facebookresearch/silk
공식 코드https://github.com/flgoyens/variety-registration
공식 코드Registration of algebraic varieties using Riemannian optimization
https://github.com/forrest-110/fastmac
공식 코드FastMAC: Stochastic Spectral Sampling of Correspondence Graph
https://github.com/fukexue/RGM
공식 코드Robust Point Cloud Registration Framework Based on Deep Graph Matching
https://github.com/gardlin/pcr-cg
공식 코드PCR-CG: Point Cloud Registration via Deep Explicit Color and Geometry
https://github.com/gdaosu/awesome-pointcloudregistration
공식 코드https://github.com/gfmei/ogmm
공식 코드Overlap-guided Gaussian Mixture Models for Point Cloud Registration
https://github.com/goldoak/spotlights
공식 코드https://github.com/guiyuzhao/vrhcf
공식 코드https://github.com/gzhang8/FractionalOrderRANSAC.jl
공식 코드https://github.com/hankyang94/damp
공식 코드https://github.com/haoyu94/coarse-to-fine-correspondences
공식 코드CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.