Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

awesome-point-cloud-analysis


https://github.com/qxiaofan/awesome-point-cloud-analysis

Last synced: 4 days ago
JSON representation

  • 2020

    • [WAD
    • [WAD
    • [nuScenes - scale autonomous driving dataset.
    • [WAD
    • [AAAI - Point-Cloud-Completion)] [__`oth.`__]
    • [AAAI
    • [AAAI - Node for Point Cloud Feature Modeling. [__`seg.`__ __`cls.`__]
    • [AAAI - Invariant Network. [__`seg.`__ __`cls.`__]
    • [CVPR
    • [CVPR - Net: Efficient Semantic Segmentation of Large-Scale Point Clouds. [[tensorflow](https://github.com/QingyongHu/RandLA-Net)] [__`seg.`__]
    • [CVPR
    • [CVPR - Net: Point Fractal Network for 3D Point Cloud Completion. [[pytorch](https://github.com/zztianzz/PF-Net-Point-Fractal-Network.git)] [__`oth.`__]
    • [CVPR - Level Context VoteNet for 3D Object Detection. [[code](https://github.com/NUAAXQ/MLCVNet)] [__`det.`__]
    • [CVPR - metric Registration: A Fast Semi-supervised Approach for Robust Point Cloud Registration without Correspondences. [[code](https://github.com/XiaoshuiHuang/fmr)] [__`reg.`__]
    • [CVPR - Equivariant Learning. [[code](https://github.com/vcg-uvic/acne)] [__`cls.`__]
    • [CVPR - net)] [__`oth.`__]
    • [CVPR - Augmentation Framework for Point Cloud Classification. [__`cls.`__]
    • [WACV - Modal Data. [__`seg.`__ __`aut.`__]
    • [arXiv
    • [ECCV
    • [ECCV - training for 3D Point Cloud Understanding. [__`cls.`__ __`seg.`__ __`det.`__]
    • [ECCV
    • [ECCV
    • [ShapeNet
    • [PartNet
    • [S3DIS - Scale 3D Indoor Spaces Dataset. [__`seg.`__]
    • [ScanNet - annotated 3D Reconstructions of Indoor Scenes. [__`cls.`__ __`seg.`__]
    • [Stanford 3D
    • [UWA Dataset
    • [Princeton Shape Benchmark
    • [ASL Datasets Repository(ETH)
    • [Large-Scale Point Cloud Classification Benchmark(ETH)
    • [Robotic 3D Scan Repository - dimensional laser scans gathered at two unique planetary analogue rover test facilities in Canada.
    • [IQmulus & TerraMobilita Contest
    • [Oakland 3-D Point Cloud Dataset - D point cloud laser data collected from a moving platform in a urban environment.
    • [Robotic 3D Scan Repository
    • [Ford Campus Vision and Lidar Data Set - 250 pickup truck.
    • [The Stanford Track Collection - 64E S2 LIDAR.
    • [WAD
    • [PreSIL - wise segmentation (point clouds), ground point labels (point clouds), and detailed annotations for all vehicles and people. [[paper](https://arxiv.org/abs/1905.00160)] [__`det.`__ __`aut.`__]
    • [PedX - resolution (12MP) stereo images and LiDAR data along with providing 2D and 3D labels of pedestrians. [[ICRA 2019 paper](https://arxiv.org/abs/1809.03605)] [__`pos.`__ __`aut.`__]
    • [Argoverse BY ARGO AI - driving vehicles how to understand the world around them.[[CVPR 2019 paper](http://openaccess.thecvf.com/content_CVPR_2019/html/Chang_Argoverse_3D_Tracking_and_Forecasting_With_Rich_Maps_CVPR_2019_paper.html)][__`tra.`__ __`aut.`__]
    • [SynthCity
    • [Lyft Level 5 - labelled 3D bounding boxes of traffic agents, an underlying HD spatial semantic map. [__`det.`__ __`seg.`__ __`aut.`__]
    • [Oxford Robotcar
    • [3D-FRONT - FUTURE](https://tianchi.aliyun.com/specials/promotion/alibaba-3d-future)] [Alibaba] 3D-FRONT contains 10,000 houses (or apartments) and ~70,000 rooms with layout information. 3D-FUTURE contains 20,000+ clean and realistic synthetic scenes in 5,000+ diverse rooms which contain 10,000+ unique high quality 3D instances of furniture.
    • [Campus3D - wisely annotated with a hierarchical structure of 24 semantic labels and contains 2,530 instances based on the labels. [[MM 2020 paper](https://arxiv.org/pdf/2008.04968.pdf)][[code](https://github.com/shinke-li/Campus3D)][ __`det.`__ __`cls.`__ __`seg.`__]
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [Ford Campus Vision and Lidar Data Set - 250 pickup truck.
    • [WAD
    • [WAD
    • [WAD
    • [PartNet
    • [WAD
    • [CVPR - Equivariant Learning. [[code](https://github.com/vcg-uvic/acne)] [__`cls.`__]
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [WAD
    • [AAAI
    • [CVPR - Net: Efficient Semantic Segmentation of Large-Scale Point Clouds. [[tensorflow](https://github.com/QingyongHu/RandLA-Net)] [__`seg.`__]
    • [CVPR - Net: Point Fractal Network for 3D Point Cloud Completion. [[pytorch](https://github.com/zztianzz/PF-Net-Point-Fractal-Network.git)] [__`oth.`__]
    • [CVPR - Level Context VoteNet for 3D Object Detection. [[code](https://github.com/NUAAXQ/MLCVNet)] [__`det.`__]
    • [CVPR - net)] [__`oth.`__]
    • [CVPR - Augmentation Framework for Point Cloud Classification. [__`cls.`__]
    • [WACV - Modal Data. [__`seg.`__ __`aut.`__]
    • [ECCV
    • [ECCV - training for 3D Point Cloud Understanding. [__`cls.`__ __`seg.`__ __`det.`__]
    • [WAD
    • [WAD
    • [WAD

  • 2019

    • [ICCV
    • [arXiv - LiDAR Point Cloud Interpolation. [__`oth.`__]
    • [ICCV
    • [CVPR - Shape Convolutional Neural Network for Point Cloud Analysis. [[pytorch](https://github.com/Yochengliu/Relation-Shape-CNN)] [__`cls.`__ __`seg.`__ __`oth.`__] :fire:
    • [CVPR
    • [CVPR
    • [CVPR - LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving. [[code](https://github.com/mileyan/pseudo_lidar)] [__`det.`__ __`dep.`__ __`aut.`__]
    • [CVPR
    • [CVPR - adv-pc)] [__`oth.`__]
    • [CVPR - Attention and Gumbel Subset Sampling. [__`cls.`__ __`seg.`__]
    • [CVPR - CNN: Annularly Convolutional Neural Networks on Point Clouds. [[tensorflow](https://github.com/artemkomarichev/a-cnn)][__`cls.`__ __`seg.`__]
    • [CVPR
    • [CVPR - Invariant Map Networks. [[tensorflow](https://github.com/zaiweizhang/path_invariance_map_network)] [__`seg.`__ __`oth.`__]
    • [CVPR - scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understanding. [[code](https://github.com/daerduoCarey/partnet_dataset)] [__`dat.`__ __`seg.`__]
    • [CVPR
    • [CVPR
    • [CVPR
    • [CVPR - ziyan/SPH3D-GCN)] [__`cls.`__ __`seg.`__]
    • [CVPR
    • [CVPR - Instance Segmentation of 3D Point Clouds with Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields. [[pytorch](https://github.com/pqhieu/JSIS3D)] [__`seg.`__]
    • [CVPR - Structured Deep Metric Learning. [__`seg.`__]
    • [CVPR
    • [CVPR - based Progressive 3D Point Set Upsampling. [[tensorflow](https://github.com/yifita/3PU)] [__`oth.`__]
    • [CVPR
    • [CVPR - grained and Hierarchical Shape Segmentation. [[pytorch](https://github.com/FoggYu/PartNet)] [__`dat.`__ __`seg.`__]
    • [CVPR
    • [CVPR - Based Randomized Approach for Robust Point Cloud Registration without Correspondences. [[matlab](https://github.com/intellhave/SDRSAC)] [__`reg.`__]
    • [CVPR - guided Progressive View Inpainting for 3D Point Scene Completion from a Single Depth Image. [__`rec.`__ __`oth.`__]
    • [CVPR
    • [CVPR - Capsule Networks. [[pytorch](https://github.com/yongheng1991/3D-point-capsule-networks)] [__`cls.`__ __`rec.`__ __`oth.`__]
    • [CVPR - Temporal ConvNets: Minkowski Convolutional Neural Networks. [[pytorch](https://github.com/StanfordVL/MinkowskiEngine)] [__`seg.`__] :fire:
    • [CVPR
    • [CVPR - Set Registration using Gaussian Filter and Twist Parameterization. [[code](https://bitbucket.org/gaowei19951004/poser/src/master/)] [__`reg.`__]
    • [CVPR
    • [CVPR - CNN. [__`cls.`__ __`det.`__]
    • [CVPR - Invariant Representation for Point Cloud Analysis. [__`cls.`__]
    • [CVPR - GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for Real-Time Point Cloud Shape Completion. [[code](https://github.com/iSarmad/RL-GAN-Net)] [__`oth.`__]
    • [CVPR - Scale Outdoor Scenes. [[code](https://github.com/ziquan111/RobustPCLReconstruction)] [__`rec.`__]
    • [CVPR - Net: Normal Estimation for Unstructured 3D Point Clouds using Convolutional Neural Networks. [[tensorflow](https://github.com/sitzikbs/Nesti-Net)] [__`oth.`__]
    • [CVPR
    • [CVPR - to-Pose Voting based Hand Pose Estimation using Residual Permutation Equivariant Layer. [__`pos.`__]
    • [CVPR
    • [CVPR - 3DCNN: Unveiling Local Phase in 3D Convolutional Neural Networks. [[project](https://sites.google.com/view/lp-3dcnn/home)] [__`cls.`__ __`seg.`__]
    • [CVPR
    • [ICCV - GAN: a Point Cloud Upsampling Adversarial Network. [[tensorflow](https://github.com/liruihui/PU-GAN)] [__`oth.`__]
    • [ICCV
    • [ICCV - Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds from Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction. [__`oth.`__]
    • [ICCV - HandNet: Self-Organizing Network for 3D Hand Pose Estimation with Semi-supervised Learning. [[code](https://github.com/TerenceCYJ/SO-HandNet)] [__`pos.`__]
    • [ICCV - Net: Denoiser and Upsampler Network for 3D Adversarial Point Clouds Defense. [__`oth.`__]
    • [ICCV - World Data. [__`cls.`__ __`dat.`__] [[code](https://github.com/hkust-vgd/scanobjectnn)] [[dataset](https://hkust-vgd.github.io/scanobjectnn/)]
    • [ICCV
    • [ICCV - vgd.github.io/shellnet/)] [__`seg.`__]
    • [ICCV - Based Multi-View Stereo Network. [[pytorch](https://github.com/callmeray/PointMVSNet)] [__`rec.`__]
    • [ICCV
    • [ICCV - to-End Deep Neural Network for 3D Point Cloud Registration. [__`reg.`__]
    • [ICCV
    • [ICCV - Edge Interaction Network for Point Cloud Semantic Segmentation. [__`seg.`__]
    • [ICCV
    • [ICCV - to-Dense 3D Object Detector for Point Cloud. [__`det.`__ __`oth.`__]
    • [ICCV - CNN. [__`det.`__ __`aut.`__]
    • [ICCVW
    • [NeurIPS - Supervised Deep Learning on Point Clouds by Reconstructing Space. [__`cls.`__ __`oth.`__]
    • [NeurIPS - Voxel CNN for Efficient 3D Deep Learning. [__`det.`__ __`seg.`__ __`aut.`__]
    • [ICLR
    • [ICMLW
    • [AAAI - iisc/capnet)] [__`rec.`__]
    • [AAAI - based Sequence to Sequence Network. [[tensorflow](https://github.com/liuxinhai/Point2Sequence)] [__`cls.`__ __`seg.`__]
    • [AAAI
    • [AAAI - View Relation Neural Network for 3D Shape Recognition. [[pytorch](https://github.com/Hxyou/PVRNet)] [__`cls.`__ __`rel.`__]
    • [TOG
    • [TOG
    • [SIGGRAPH Asia
    • [arvix - Point-Cloud)] [__`cls.`__ __`det.`__ __`tra.`__ __`seg.`__]
    • [arXiv - GANs for High-Resolution 3D Point-cloud Generation. [__`rec.`__ __`oth.`__]
    • [arXiv
    • [ICME
    • [ICASSP - Projection)] [__`oth.`__]
    • [BMVC - Shot Learning of 3D Objects. [__`cls.`__]
    • [ICRA - equ-net)] [__`cls.`__]
    • [ICRA - Object Segmentation from a LiDAR Point Cloud. [[tensorflow](https://github.com/xuanyuzhou98/SqueezeSegV2)] [__`seg.`__ __`aut.`__]
    • [ICRA
    • [ICRA
    • [ICRA - cloud-compression-by-RNN)] [__`oth.`__]
    • [ICRA - ram/FL3D)] [__`det.`__ __`aut.`__]
    • [ICRA
    • [ICRA - MatchNet: Learning to Match Keypoints across 2D Image and 3D Point Cloud. [__`oth.`__]
    • [ICRA - scale 5D Semantics Benchmark for Autonomous Driving. [[project](https://github.com/VCCIV/BLVD)] [__`dat.`__ __`det.`__ __`tra.`__ __`aut.`__ __`oth.`__]
    • [ICRA - overlap 3-D point cloud registration for outlier rejection. [[matlab](https://github.com/JStech/ICP)] [__`reg.`__]
    • [ICRA
    • [ICRA
    • [ICRA - Net: Multimodal VoxelNet for 3D Object Detection. [__`det.`__ __`aut.`__]
    • [ICRA - 3D: Estimating the Covariance of ICP in the Real World. [__`reg.`__]
    • [IROS - Aware PointNet for Object Recognition from Multi-View 2.5D Point Clouds. [[tensorflow](https://github.com/Merium88/Edge-Aware-PointNet)] [__`cls.`__ __`det.`__]
    • [IROS - Closure Detection Based on Large-Scale Point Cloud Description for Self-Driving Vehicles. [__`oth.`__] [__`aut.`__]
    • [IROS
    • [IV - to-End 3D-PointCloud Semantic Segmentation for Autonomous Driving. [__`seg.`__] [__`aut.`__]
    • [Eurographics Workshop
    • [WACV
    • [3DV - vgd.github.io/riconv/)] [__`cls.`__ __`seg.`__]
    • [3DV - invariant Point CNN with Spherical Harmonics kernels. [[tensorflow](https://github.com/adrienPoulenard/SPHnet)] [__`cls.`__ __`seg.`__ __`oth.`__]
    • [TVCG - Selection of 3D Point Clouds. [[project](https://lassonet.github.io/)] [__`oth.`__]
    • [arXiv
    • [arXiv - Cloud Saliency Maps. [[tensorflow](https://github.com/tianzheng4/PointCloud-Saliency-Maps)] [__`cls.`__ __`oth.`__]
    • [arXiv - Liu-c0deb0t/3D-Neural-Network-Adversarial-Attacks)] [__`oth.`__]
    • [arxiv
    • [arXiv - Cloud to Image Translation using conditional Generative Adversarial Networks. [__`oth.`__]
    • [arXiv - Encoder and Sampler. [__`cls.`__ __`oth.`__]
    • [arXiv - aware Loss Function for Point Cloud Semantic Instance Segmentation. [__`seg.`__]
    • [arXiv - shot Learning of 3D Point Cloud Objects. [[code](https://github.com/alichr/Zero-shot-Learning-of-3D-Point-Cloud-Objects)] [__`cls.`__]
    • [arXiv - LiDAR Point Cloud. [__`det.`__ __`aut.`__]
    • [arXiv - time Multiple People Hand Localization in 4D Point Clouds. [__`det.`__ __`oth.`__]
    • [arXiv
    • [arXiv
    • [arXiv
    • [arXiv - View Proposal Generation for Real-Time Object Detection from Point Clouds. [[code](https://github.com/LordLiang/FVNet)] [__`det.`__ __`aut.`__]
    • [arXiv
    • [arXiv - Supervised Learning of Local Features in 3D Point Clouds. [__`cls.`__ __`seg.`__]
    • [arXiv
    • [arXiv - YOLO: Real-Time 3D Object Detection and Tracking on Semantic Point Clouds. [[pytorch](https://github.com/AI-liu/Complex-YOLO)] [__`det.`__ __`tra.`__ __`aut.`__] :fire:
    • [arXiv - based Inpainting for 3D Dynamic Point Clouds. [__`oth.`__]
    • [arXiv
    • [arXiv
    • [arXiv - AAE)] [__`rel.`__ __`oth.`__]
    • [arXiv
    • [arXiv
    • [arXiv - based Geometry Processing. [[pytorch](https://github.com/yifita/DSS)] [__`oth.`__]
    • [arXiv
    • [arXiv - Voxel CNN for Efficient 3D Deep Learning. [__`seg.`__ __`det.`__ __`aut.`__]
    • [arXiv - Based Graphics. [[project](https://dmitryulyanov.github.io/neural_point_based_graphics)] [__`oth.`__]
    • [arXiv
    • [arXiv
    • [arXiv
    • [arXiv - 3D Siamese Networks on LIDAR. [__`tra.`__]
    • [arXiv
    • [arXiv - A^2 Net: 3D Part-Aware and Aggregation Neural Network for Object Detection from Point Cloud. [__`det.`__ __`aut.`__]
    • [arXiv
    • [arXiv
    • [arXiv - Decoder with Point Atrous Convolution for Unorganized 3D Points. [[tensorflow](https://github.com/paul007pl/PointAtrousGraph)] [__`cls.`__ __`seg.`__]
    • [arXiv
    • [arXiv - Rotation-Equivariant Quaternion Neural Networks. [__`cls.`__ __`rec.`__]
    • [arXiv - aware Capsules. [__`cls.`__ __`rel.`__ __`seg.`__]
    • [arXiv
    • [arXiv
    • [arXiv
    • [arXiv - GCN: Point Cloud Upsampling via Graph Convolutional Network. [[project](https://sites.google.com/kaust.edu.sa/pugcn)] [__`oth.`__]
    • [arXiv
    • [arXiv - GCN for Fast and Scalable Point Cloud Learning. [__`seg.`__ __`cls.`__]
    • [arXiv
    • [arXiv - Shot Learning for 3D Point Cloud Classification. [__`cls.`__]
    • [arXiv - Net)] [__`cls.`__ __`seg.`__]
    • [arXiv - -- A Study of Point Cloud-Based Deep Learning Models. [__`cls.`__ __`det.`__]
    • [MM - Invariant Representations for Point Cloud Classification and Segmentation. [[tensorflow](https://github.com/tasx0823/SRINet)] [__`cls.`__ __`seg.`__]
    • [MM - encoder: Understanding Point Clouds by Local-to-Global Reconstruction with Hierarchical Self-Attention. [__`cls.`__ __`rel.`__]
    • [MM - Aware Point Cloud Semantic Segmentation for Autonomous Driving. [[code](https://github.com/Jaiy/Ground-aware-Seg)] [__`seg.`__ __`aut.`__]
    • [ICRA
    • [ICCV - Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds from Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction. [__`oth.`__]
    • [ICCV - Edge Interaction Network for Point Cloud Semantic Segmentation. [__`seg.`__]
    • [IROS - Closure Detection Based on Large-Scale Point Cloud Description for Self-Driving Vehicles. [__`oth.`__] [__`aut.`__]
    • [arXiv
    • [arXiv - Rotation-Equivariant Quaternion Neural Networks. [__`cls.`__ __`rec.`__]
    • [arXiv - aware Capsules. [__`cls.`__ __`rel.`__ __`seg.`__]
    • [arXiv - GCN: Point Cloud Upsampling via Graph Convolutional Network. [[project](https://sites.google.com/kaust.edu.sa/pugcn)] [__`oth.`__]
    • [SIGGRAPH Asia - Net: recurrent prediction of motion and parts from point cloud. [[tensorflow](https://github.com/Salingo/RPM-Net)] [__`seg.`__]
    • [ICCV
    • [CVPR
    • [CVPR - scale Point Clouds. [[pytorch](https://github.com/laoreja/HPLFlowNet)] [__`oth.`__]
    • [ICCV
    • [arXiv - BoNet)] [__`det.`__ __`seg.`__]
    • [ICCV - Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis. [__`oth.`__ __`aut.`__]
    • [NeurIPS - Voxel CNN for Efficient 3D Deep Learning. [__`det.`__ __`seg.`__ __`aut.`__]
    • [TOG
    • [MM - Modal Joint Networks for 3D Shape Recognition. [__`cls.`__ __`rel.`__]
    • [NeurIPS - Supervised Deep Learning on Point Clouds by Reconstructing Space. [__`cls.`__ __`oth.`__]
    • [MM
    • [arXiv
    • [arXiv
    • [arXiv
    • [arXiv
    • [arXiv
    • [arXiv
    • [arXiv
    • [arXiv - GCN for Fast and Scalable Point Cloud Learning. [__`seg.`__ __`cls.`__]
    • [arXiv
    • [arXiv - Shot Learning for 3D Point Cloud Classification. [__`cls.`__]
    • [arXiv - Net)] [__`cls.`__ __`seg.`__]
    • [arXiv - LiDAR Point Cloud Interpolation. [__`oth.`__]
    • [3DV - vgd.github.io/riconv/)] [__`cls.`__ __`seg.`__]
    • [TVCG - Selection of 3D Point Clouds. [[project](https://lassonet.github.io/)] [__`oth.`__]
    • [CVPR - Based Localization. [__`pos.`__ __`oth.`__]
    • [CVPRW - Object Detection in Point Clouds. [[pytorch](https://github.com/anshulpaigwar/Attentional-PointNet)] [__`cls.`__ __`det.`__ __`aut.`__]
    • [ICCV
    • [ICCV
    • [ICCV - Saliency-Maps)] [__`oth.`__]
    • [ICCV - to-Dense 3D Object Detector for Point Cloud. [__`det.`__ __`oth.`__]
    • [ICCV - Task Feature Learning on Point Clouds. [__`cls.`__ __`seg.`__]
    • [ICCV - Convolution for Point Cloud Deformation in 2D-to-3D Conversion. [[pytorch](https://github.com/justanhduc/graphx-conv)] [__`rec.`__]
    • [ICCV
    • [arXiv

  • 2018

    • [ICRA
    • [arXiv - column Point-CNN for Sketch Segmentation. [__`seg.`__]
    • [AAAI - point-cloud-generation)] [__`rec.`__] :fire:
    • [AAAI
    • [ICML
    • [SIGGRAPH - NET: Bidirectional Point Displacement Net for Shape Transform. [[tensorflow](https://github.com/kangxue/P2P-NET)] [__`oth.`__]
    • [SIGGRAPH Asia - Uniformly Sampled Point Clouds. [[tensorflow](https://github.com/viscom-ulm/MCCNN)] [__`cls.`__ __`seg.`__ __`oth.`__]
    • [SIGGRAPH - view convolutional networks. [[project](https://people.cs.umass.edu/~hbhuang/local_mvcnn/index.html)] [__`seg.`__ __`oth.`__]
    • [MM - View for 3D Shape Recognition. [__`cls.`__ __`rel.`__]
    • [MM
    • [MM - based Layered Structure and Block-based Intra Prediction. [__`oth.`__]
    • [ICRA - to-end Learning of Multi-sensor 3D Tracking by Detection. [__`det.`__ __`tra.`__ __`aut.`__]
    • [ICRA - View 3D Entangled Forest for Semantic Segmentation and Mapping. [__`seg.`__ __`oth.`__]
    • [ICRA - Time Road-Object Segmentation from 3D LiDAR Point Cloud. [[tensorflow](https://github.com/priyankanagaraj1494/Squeezseg)] [__`seg.`__ __`aut.`__]
    • [ICRA - Time 3D Person Detection for Indoor and Outdoor Applications. [__`det.`__]
    • [ICRA - Precision Depth Estimation with the 3D LiDAR and Stereo Fusion. [__`dep.`__ __`aut.`__]
    • [ICRA - Point Network for Classification of Deformed Building Element Point Clouds. [__`cls.`__]
    • [ICRA - Guided Geometry Extraction from Point Clouds. [__`oth.`__]
    • [ICRA
    • [ICRA
    • [ICRA
    • [ICRA
    • [ICRA - Based Exploration for Autonomous 3D Modeling. [__`oth.`__ __`aut.`__]
    • [ICRA
    • [ICRA - Net 3.0: Computing Robust Vacuum Suction Grasp Targets in Point Clouds Using a New Analytic Model and Deep Learning. [__`oth.`__]
    • [ICRA - Time Object Tracking in Sparse Point Clouds Based on 3D Interpolation. [__`tra.`__]
    • [ICRA
    • [ICRA - Cue Photometric Point Cloud Registration. [__`reg.`__]
    • [ICRA - Time SLAM for 3D Lidar-Based Online Mapping. [__`oth.`__]
    • [ICRA - LiDAR System. [__`oth.`__]
    • [ICRA
    • [ICRA - Sensor Fusion for 3D Mapping and Localization. [__`oth.`__]
    • [ICRA
    • [IROS
    • [IROS
    • [IROS - Photogrammetry with Random Patterns. [__`rec.`__ __`oth.`__]
    • [IROS
    • [IROS
    • [IROS - Environment 3D LiDAR Localization. [__`oth.`__]
    • [IROS
    • [IROS - LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain.[[code](https://github.com/RobustFieldAutonomyLab/LeGO-LOAM)] [__`pos.`__ __`oth.`__] :fire:
    • [IROS
    • [IROS
    • [IROS
    • [IROS
    • [IROS - Cost RGB-D Sensor. [[code](https://github.com/CTTCGeoLab/VI_ROS)][__`oth.`__]
    • [IROS - Time Amodal 3D Object Detection. [__`det.`__ __`pos.`__]
    • [IROS
    • [IROS
    • [IROS - Net)]3DmFV: Point Cloud Classification and segmentation for unstructured 3D point clouds. [__`cls.`__ ]
    • [IROS
    • [SENSORS
    • [ACCV - Convolution (Million-Scale Point-Cloud Learning Beyond Grid-Worlds). [[tensorflow](https://github.com/cgtuebingen/Flex-Convolution)] [__`seg.`__]
    • [3DV
    • [ICASSP - CNN for 3D Point Cloud Classification. [[tensorflow](https://github.com/maggie0106/Graph-CNN-in-3D-Point-Cloud-Classification)] [__`cls.`__] :fire:
    • [ITSC
    • [arXiv - like Network Module for 3D Point Cloud Semantic Segmentation. [[tensorflow](https://github.com/MVIG-SJTU/pointSIFT)] [__`seg.`__] :fire:
    • [arXiv
    • [arXiv
    • [arXiv
    • [arXiv - Aware Surface Reconstruction for Point Clouds. [__`rec.`__]
    • [arXiv
    • [arXiv
    • [arXiv - based Object Detector for Point Cloud. [__`det.`__]
    • [arXiv - controllable Point Cloud Simplification on Graph. [__`oth.`__]
    • [arXiv
    • [arXiv - YOLO: Real-time 3D Object Detection on Point Clouds. [[pytorch](https://github.com/AI-liu/Complex-YOLO)] [__`det.`__ __`aut.`__] :fire:
    • [arxiv
    • [arXiv - Attention. [[project](https://liuziwei7.github.io/projects/PointGrow)] [__`oth.`__]
    • [arXiv - Cloud-GAN)] [__`oth.`__]
    • [ICRA - to-end Learning of Multi-sensor 3D Tracking by Detection. [__`det.`__ __`tra.`__ __`aut.`__]
    • [ICRA - View 3D Entangled Forest for Semantic Segmentation and Mapping. [__`seg.`__ __`oth.`__]
    • [ICRA - Time Road-Object Segmentation from 3D LiDAR Point Cloud. [[tensorflow](https://github.com/priyankanagaraj1494/Squeezseg)] [__`seg.`__ __`aut.`__]
    • [ICRA - Time 3D Person Detection for Indoor and Outdoor Applications. [__`det.`__]
    • [ICRA - Precision Depth Estimation with the 3D LiDAR and Stereo Fusion. [__`dep.`__ __`aut.`__]
    • [ICRA - Point Network for Classification of Deformed Building Element Point Clouds. [__`cls.`__]
    • [ICRA - Guided Geometry Extraction from Point Clouds. [__`oth.`__]
    • [ICRA
    • [ICRA
    • [ICRA
    • [ICRA
    • [ICRA - Based Exploration for Autonomous 3D Modeling. [__`oth.`__ __`aut.`__]
    • [ICRA - Net 3.0: Computing Robust Vacuum Suction Grasp Targets in Point Clouds Using a New Analytic Model and Deep Learning. [__`oth.`__]
    • [ICRA - Time Object Tracking in Sparse Point Clouds Based on 3D Interpolation. [__`tra.`__]
    • [ICRA
    • [ICRA - Cue Photometric Point Cloud Registration. [__`reg.`__]
    • [ICRA - Time SLAM for 3D Lidar-Based Online Mapping. [__`oth.`__]
    • [ICRA - LiDAR System. [__`oth.`__]
    • [ICRA
    • [ICRA - Sensor Fusion for 3D Mapping and Localization. [__`oth.`__]
    • [ICRA
    • [IROS
    • [IROS
    • [IROS - Photogrammetry with Random Patterns. [__`rec.`__ __`oth.`__]
    • [IROS
    • [IROS
    • [IROS - Environment 3D LiDAR Localization. [__`oth.`__]
    • [IROS
    • [IROS - LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain.[[code](https://github.com/RobustFieldAutonomyLab/LeGO-LOAM)] [__`pos.`__ __`oth.`__] :fire:
    • [IROS
    • [IROS
    • [IROS
    • [IROS
    • [IROS - Cost RGB-D Sensor. [[code](https://github.com/CTTCGeoLab/VI_ROS)][__`oth.`__]
    • [IROS - Time Amodal 3D Object Detection. [__`det.`__ __`pos.`__]
    • [IROS
    • [IROS
    • [IROS
    • [CVPR
    • [CVPR - Pointnet)] [__`pos.`__]
    • [CVPR
    • [ECCV
    • [ICRA - to-end Learning of Multi-sensor 3D Tracking by Detection. [__`det.`__ __`tra.`__ __`aut.`__]
    • [ICRA - View 3D Entangled Forest for Semantic Segmentation and Mapping. [__`seg.`__ __`oth.`__]
    • [ICRA - Time 3D Person Detection for Indoor and Outdoor Applications. [__`det.`__]
    • [ICRA - Precision Depth Estimation with the 3D LiDAR and Stereo Fusion. [__`dep.`__ __`aut.`__]
    • [ICRA - Point Network for Classification of Deformed Building Element Point Clouds. [__`cls.`__]
    • [ICRA - Guided Geometry Extraction from Point Clouds. [__`oth.`__]
    • [ICRA
    • [ICRA
    • [ICRA
    • [ICRA - Based Exploration for Autonomous 3D Modeling. [__`oth.`__ __`aut.`__]
    • [ICRA
    • [ICRA - Net 3.0: Computing Robust Vacuum Suction Grasp Targets in Point Clouds Using a New Analytic Model and Deep Learning. [__`oth.`__]
    • [ICRA - Time Object Tracking in Sparse Point Clouds Based on 3D Interpolation. [__`tra.`__]
    • [ICRA
    • [ICRA - Cue Photometric Point Cloud Registration. [__`reg.`__]
    • [ICRA - Time SLAM for 3D Lidar-Based Online Mapping. [__`oth.`__]
    • [ICRA - LiDAR System. [__`oth.`__]
    • [ICRA
    • [ICRA - Sensor Fusion for 3D Mapping and Localization. [__`oth.`__]
    • [IROS
    • [IROS
    • [IROS - Photogrammetry with Random Patterns. [__`rec.`__ __`oth.`__]
    • [IROS
    • [IROS
    • [IROS - Environment 3D LiDAR Localization. [__`oth.`__]
    • [IROS
    • [IROS - LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain.[[code](https://github.com/RobustFieldAutonomyLab/LeGO-LOAM)] [__`pos.`__ __`oth.`__] :fire:
    • [IROS
    • [IROS
    • [IROS
    • [IROS - Cost RGB-D Sensor. [[code](https://github.com/CTTCGeoLab/VI_ROS)][__`oth.`__]
    • [IROS - Time Amodal 3D Object Detection. [__`det.`__ __`pos.`__]
    • [IROS
    • [IROS
    • [IROS
    • [CVPR - Scale Place Recognition. [[tensorflow](https://github.com/mikacuy/pointnetvlad.git)] [__`rel.`__] :fire:
    • [CVPR
    • [ICRA - to-end Learning of Multi-sensor 3D Tracking by Detection. [__`det.`__ __`tra.`__ __`aut.`__]
    • [ICRA - View 3D Entangled Forest for Semantic Segmentation and Mapping. [__`seg.`__ __`oth.`__]
    • [ICRA - Time 3D Person Detection for Indoor and Outdoor Applications. [__`det.`__]
    • [ICRA - Precision Depth Estimation with the 3D LiDAR and Stereo Fusion. [__`dep.`__ __`aut.`__]
    • [ICRA - Point Network for Classification of Deformed Building Element Point Clouds. [__`cls.`__]
    • [ICRA - Guided Geometry Extraction from Point Clouds. [__`oth.`__]
    • [ICRA
    • [ICRA
    • [ICRA
    • [ICRA - Based Exploration for Autonomous 3D Modeling. [__`oth.`__ __`aut.`__]
    • [ICRA - Net 3.0: Computing Robust Vacuum Suction Grasp Targets in Point Clouds Using a New Analytic Model and Deep Learning. [__`oth.`__]
    • [ICRA - Time Object Tracking in Sparse Point Clouds Based on 3D Interpolation. [__`tra.`__]
    • [ICRA
    • [ICRA - LiDAR System. [__`oth.`__]
    • [ICRA
    • [ICRA - Cue Photometric Point Cloud Registration. [__`reg.`__]
    • [ICRA - Time SLAM for 3D Lidar-Based Online Mapping. [__`oth.`__]
    • [ICRA - Sensor Fusion for 3D Mapping and Localization. [__`oth.`__]
    • [IROS
    • [IROS
    • [IROS - Photogrammetry with Random Patterns. [__`rec.`__ __`oth.`__]
    • [IROS
    • [IROS
    • [IROS - Environment 3D LiDAR Localization. [__`oth.`__]
    • [IROS
    • [IROS - LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain.[[code](https://github.com/RobustFieldAutonomyLab/LeGO-LOAM)] [__`pos.`__ __`oth.`__] :fire:
    • [IROS
    • [IROS
    • [IROS
    • [IROS - Cost RGB-D Sensor. [[code](https://github.com/CTTCGeoLab/VI_ROS)][__`oth.`__]
    • [IROS - Time Amodal 3D Object Detection. [__`det.`__ __`pos.`__]
    • [IROS
    • [IROS
    • [IROS
    • [ICRA - to-end Learning of Multi-sensor 3D Tracking by Detection. [__`det.`__ __`tra.`__ __`aut.`__]
    • [ICRA - View 3D Entangled Forest for Semantic Segmentation and Mapping. [__`seg.`__ __`oth.`__]
    • [ICRA - Time 3D Person Detection for Indoor and Outdoor Applications. [__`det.`__]
    • [ICRA - Precision Depth Estimation with the 3D LiDAR and Stereo Fusion. [__`dep.`__ __`aut.`__]
    • [ICRA - Point Network for Classification of Deformed Building Element Point Clouds. [__`cls.`__]
    • [ICRA - Guided Geometry Extraction from Point Clouds. [__`oth.`__]
    • [ICRA
    • [ICRA
    • [ICRA
    • [ICRA - Based Exploration for Autonomous 3D Modeling. [__`oth.`__ __`aut.`__]
    • [ICRA - Net 3.0: Computing Robust Vacuum Suction Grasp Targets in Point Clouds Using a New Analytic Model and Deep Learning. [__`oth.`__]
    • [ICRA - Time Object Tracking in Sparse Point Clouds Based on 3D Interpolation. [__`tra.`__]
    • [ICRA
    • [ICRA - Cue Photometric Point Cloud Registration. [__`reg.`__]
    • [ICRA - Time SLAM for 3D Lidar-Based Online Mapping. [__`oth.`__]
    • [ICRA - LiDAR System. [__`oth.`__]
    • [ICRA
    • [ICRA - Sensor Fusion for 3D Mapping and Localization. [__`oth.`__]
    • [IROS - Photogrammetry with Random Patterns. [__`rec.`__ __`oth.`__]
    • [IROS
    • [IROS
    • [IROS
    • [IROS
    • [IROS - Environment 3D LiDAR Localization. [__`oth.`__]
    • [IROS
    • [IROS - LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain.[[code](https://github.com/RobustFieldAutonomyLab/LeGO-LOAM)] [__`pos.`__ __`oth.`__] :fire:
    • [IROS
    • [IROS
    • [IROS
    • [IROS - Cost RGB-D Sensor. [[code](https://github.com/CTTCGeoLab/VI_ROS)][__`oth.`__]
    • [IROS - Time Amodal 3D Object Detection. [__`det.`__ __`pos.`__]
    • [IROS
    • [IROS
    • [IROS
    • [TOG
    • [ITSC
    • [arXiv - Cloud-GAN)] [__`oth.`__]

  • 2017

Categories
2018 220 2019 198 2020 96 2017 17
Sub Categories