https://github.com/luxiya01/mbes-registration-data
공식 코드Benchmarking Classical and Learning-Based Multibeam Point Cloud Registration
Papers with Code 아카이브
3D Point Cloud Interpolation
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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/maanighaffari/c-sensor-registration
공식 코드https://github.com/mahdi-slh/Graphite
공식 코드Graphite: GRAPH-Induced feaTure Extraction for Point Cloud Registration
https://github.com/marineroboticsgroup/dcsam
공식 코드https://github.com/mbanani/unsupervisedRR
공식 코드UnsupervisedR&R: Unsupervised Point Cloud Registration via Differentiable Rendering
https://github.com/mcdermatt/icet
공식 코드ICET Online Accuracy Characterization for Geometry-Based Laser Scan Matching
https://github.com/megvii-research/FINet
공식 코드FINet: Dual Branches Feature Interaction for Partial-to-Partial Point Cloud Registration
https://github.com/megvii-research/omnet
공식 코드OMNet: Learning Overlapping Mask for Partial-to-Partial Point Cloud Registration
https://github.com/mhorn11/deepclr
공식 코드DeepCLR: Correspondence-Less Architecture for Deep End-to-End Point Cloud Registration
https://github.com/minghanz/equivreg
공식 코드Correspondence-Free Point Cloud Registration with SO(3)-Equivariant Implicit Shape Representations
https://github.com/minnjung/ep2p-loc
공식 코드EP2P-Loc: End-to-End 3D Point to 2D Pixel Localization for Large-Scale Visual Localization
https://github.com/mit-acl/clipper
공식 코드CLIPPER: A Graph-Theoretic Framework for Robust Data Association
https://github.com/mit-spark/buffer-x
공식 코드BUFFER-X: Towards Zero-Shot Point Cloud Registration in Diverse Scenes
https://github.com/mit-spark/kiss-matcher
공식 코드KISS-Matcher: Fast and Robust Point Cloud Registration Revisited
https://github.com/muhammadsaeedbatikh/knn-res_demo
공식 코드kNN-Res: Residual Neural Network with kNN-Graph coherence for point cloud registration
https://github.com/multimodallearning/deep-geo-reg
공식 코드https://github.com/multimodallearning/denoised_mt_pcd_reg
공식 코드A denoised Mean Teacher for domain adaptive point cloud registration
https://github.com/muyao99/tfct-i2p
공식 코드https://github.com/neu-vi/superpoints_registration
공식 코드A Strong Baseline for Point Cloud Registration via Direct Superpoints Matching
https://github.com/numerical-geometric-algebra/registrationga
공식 코드Correspondence Free Multivector Cloud Registration using Conformal Geometric Algebra
https://github.com/omron-sinicx/weavenet
공식 코드3D Point Cloud Registration with Learning-based Matching Algorithm
https://github.com/paul007pl/MVP_Benchmark
공식 코드https://github.com/paul007pl/gmcnet
공식 코드Robust Partial-to-Partial Point Cloud Registration in a Full Range
https://github.com/peakpang/ugp
공식 코드Unlocking Generalization Power in LiDAR Point Cloud Registration
https://github.com/peterstratton/volume-droid
공식 코드Volume-DROID: A Real-Time Implementation of Volumetric Mapping with DROID-SLAM
https://github.com/phdymz/pointclm
공식 코드PointCLM: A Contrastive Learning-based Framework for Multi-instance Point Cloud Registration
https://github.com/phdymz/pointmbf
공식 코드PointMBF: A Multi-scale Bidirectional Fusion Network for Unsupervised RGB-D Point Cloud Registration
https://github.com/pranavkdm/R-PointHop
공식 코드R-PointHop: A Green, Accurate, and Unsupervised Point Cloud Registration Method
https://github.com/qiaozhijian/VCR-Net
공식 코드End-to-End 3D Point Cloud Learning for Registration Task Using Virtual Correspondences
https://github.com/qinzheng93/geotransformer
공식 코드Geometric Transformer for Fast and Robust Point Cloud Registration
https://github.com/qinzheng93/graphscnet
공식 코드Deep Graph-based Spatial Consistency for Robust Non-rigid Point Cloud Registration
https://github.com/rabbityl/deformationpyramid
공식 코드Non-rigid Point Cloud Registration with Neural Deformation Pyramid
https://github.com/rabbityl/lepard
공식 코드Lepard: Learning partial point cloud matching in rigid and deformable scenes
https://github.com/renlanghuang/cast
공식 코드A Consistency-Aware Spot-Guided Transformer for Versatile and Hierarchical Point Cloud Registration
https://github.com/rlit/LatentRANSAC
공식 코드https://github.com/robot-learning-freiburg/LCDNet
공식 코드LCDNet: Deep Loop Closure Detection and Point Cloud Registration for LiDAR SLAM
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.