https://github.com/cuge1995/eccv-2020-point-cloud-analysis

ECCV 2020 papers focusing on point cloud analysis
https://github.com/cuge1995/eccv-2020-point-cloud-analysis

deep-learning eccv-2020 point point-cloud pointcloud

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ECCV 2020 papers focusing on point cloud analysis

• Host: GitHub
• URL: https://github.com/cuge1995/eccv-2020-point-cloud-analysis
• Owner: cuge1995
• Created: 2020-07-04T01:34:19.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2021-04-10T02:20:29.000Z (about 5 years ago)
• Last Synced: 2025-03-02T10:26:22.203Z (about 1 year ago)
• Topics: deep-learning, eccv-2020, point, point-cloud, pointcloud
• Homepage:
• Size: 27.3 KB
• Stars: 22
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# ECCV-2020-point-cloud-analysis

ECCV 2020 papers focusing on point cloud analysis

- [CAD-Deform: Deformable Fitting of CAD Models to 3D Scans.](https://arxiv.org/pdf/2007.11965.pdf)  ` CAD reconstruction ` 

  - [[Code](https://github.com/alexeybokhovkin/CAD-Deform)]

- [Weakly Supervised 3D Object Detection from Lidar Point Cloud.](https://arxiv.org/pdf/2007.11901.pdf)  ` object detection ` 

  - [[Code](https://github.com/hlesmqh/WS3D)]

- [AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds.](https://arxiv.org/abs/1912.00461)  ` attack ` 

  - [[Code](https://github.com/ajhamdi/AdvPC)]

- [Learning Graph-Convolutional Representations for Point Cloud Denoising.](https://arxiv.org/abs/2007.02578)  ` denoising ` 

  - [[Code](https://github.com/diegovalsesia/GPDNet)]

- [Detail Preserved Point Cloud Completion via Separated Feature Aggregation.](https://arxiv.org/pdf/2007.02374.pdf)  ` completion ` 

  - [[Code](https://github.com/XLechter/Detail-Preserved-Point-Cloud-Completion-via-SFA)]

- [GRNet: Gridding Residual Network for Dense Point Cloud Completion.](https://arxiv.org/abs/2006.03761)  ` completion ` 

  - [[Code](https://github.com/hzxie/GRNet)]

- [EPNet: Enhancing Point Features with Image Semantics for 3D Object Detection.]()  ` detection ` 

  - [[Code](https://github.com/happinesslz/EPNet)]

- [3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for 3D Object Detection.](https://arxiv.org/pdf/2004.12636.pdf)  ` detection ` 

  - [[Code](https://github.com/rasd3/3D-CVF)]

- [PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding.](https://arxiv.org/pdf/2007.10985.pdf)  ` representation learning `  

  - [[Code](https://github.com/facebookresearch/PointContrast)]

- [Finding Your (3D) Center: 3D Object Detection Using a Learned Loss.](https://arxiv.org/abs/2004.02693)  ` detection ` 

  - [[Code](https://github.com/dgriffiths3/finding-your-center)]

- [H3DNet: 3D Object Detection Using Hybrid Geometric Primitives.](https://arxiv.org/pdf/2006.05682.pdf)  ` detection ` 

  - [[Code](https://github.com/zaiweizhang/H3DNet)]

- [Progressive Point Cloud Deconvolution Generation Network.](https://arxiv.org/pdf/2007.05361.pdf)  ` generation ` 

  - [[Code](https://github.com/fpthink/PDGN)]

- [Label-Efficient Learning on Point Clouds using Approximate Convex Decompositions.](https://arxiv.org/abs/2003.13834.pdf)  ` segmentation ` 

  - [[Code](https://github.com/matheusgadelha/PointCloudLearningACD)]

- [SSN: Shape Signature Networks for Multi-class Object Detection from Point Clouds.](https://arxiv.org/abs/2004.02774)  ` detection ` 

  - [[Code](https://github.com/xinge008/SSN)]

- [DPDist : Comparing Point Clouds Using Deep Point Cloud Distance.](https://arxiv.org/abs/2004.11784.pdf)  ` distance ` 

  - [[Code](https://github.com/dahliau/DPDist)]

- [A Closer Look at Local Aggregation Operators in Point Cloud Analysis.](https://arxiv.org/abs/2007.01294)  ` classification `  ` segmentation ` 

  - [[Code](https://github.com/zeliu98/CloserLook3D)]

- [Quaternion Equivariant Capsule Networks for 3D Point Clouds.](https://arxiv.org/pdf/1912.12098.pdf)  ` classification ` 

  - [[Code](https://github.com/tolgabirdal/qenetworks)]

- [ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds.](https://arxiv.org/abs/2003.12181.pdf)  ` Fitting `  

  - [[Code](https://github.com/Hippogriff/parsenet-codebase)]

- [PUGeo-Net: A Geometry-centric Network for 3D Point Cloud Upsampling.](https://arxiv.org/pdf/2002.10277.pdf)  ` upsampling `  

  - [[Code](https://github.com/ninaqy/PUGeo)]

- [PointPWC-Net: Cost Volume on Point Clouds for (Self-)Supervised Scene Flow Estimation.](https://arxiv.org/abs/1911.12408)  ` flow `  

  - [[Code](https://github.com/DylanWusee/PointPWC)]

- [Points2Surf: Learning Implicit Surfaces from Point Cloud Patches.](https://arxiv.org/pdf/2007.10453.pdf)  ` surface reconstruction `  

  - [[Code](https://github.com/ErlerPhilipp/points2surf)]

- [Weakly-supervised 3D Shape Completion in the Wild.](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500273.pdf)   ` completion ` 

- [Discrete Point Flow Networks for Efficient Point Cloud Generation.](https://arxiv.org/abs/2007.10170)  ` generation `  

  - [[Code](https://github.com/Regenerator/dpf-nets)]