https://github.com/cuge1995/iccv-2021-point-cloud-analysis

ICCV 2021 papers and code focus on point cloud analysis
https://github.com/cuge1995/iccv-2021-point-cloud-analysis

3d-object-detection deep-learning point-cloud-detection point-cloud-registration point-cloud-segmentation

Last synced: 8 months ago
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ICCV 2021 papers and code focus on point cloud analysis

• Host: GitHub
• URL: https://github.com/cuge1995/iccv-2021-point-cloud-analysis
• Owner: cuge1995
• Created: 2021-08-07T12:30:02.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2021-10-21T08:13:33.000Z (about 4 years ago)
• Last Synced: 2025-01-12T22:33:01.309Z (9 months ago)
• Topics: 3d-object-detection, deep-learning, point-cloud-detection, point-cloud-registration, point-cloud-segmentation
• Homepage:
• Size: 15.6 KB
• Stars: 15
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# ICCV-2021-point-cloud-analysis

ICCV 2021 papers and code focus on point cloud analysis

- [Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis](https://arxiv.org/abs/2105.01288) `classification` 

  - [[Code](https://github.com/tiangexiang/CurveNet)]

- [Score-Based Point Cloud Denoising](https://arxiv.org/abs/2107.10981) `Denoising`

  - [[Code](https://github.com/luost26/score-denoise)]

- [ReDAL: Region-based and Diversity-aware Active Learning for Point Cloud Semantic Segmentation](https://arxiv.org/abs/2107.11769) `Segmentation`

- [HRegNet: A Hierarchical Network for Large-scale Outdoor LiDAR Point Cloud Registration](https://arxiv.org/abs/2107.11992) `registration`

  - [[Code](https://ispc-group.github.io/hregnet)]

- [Learning with Noisy Labels for Robust Point Cloud Segmentation](https://arxiv.org/abs/2107.14230) `segmentation` `oral`

  - [[Code](https://shuquanye.com/PNAL_website/)]

- [Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentation](https://arxiv.org/abs/2107.14724) `segmentation` `Domain Adaptation`

  - [[Code](https://github.com/leolyj/DsCML)]

 

- [Unsupervised Point Cloud Pre-Training via View-Point Occlusion, Completion](https://arxiv.org/abs/2010.01089) `Unsupervised learning`

  - [[Code](https://github.com/hansen7/OcCo)]

- [Group-Free 3D Object Detection via Transformers](https://arxiv.org/abs/2104.00678) `3D Object Detection`

- [Hierarchical Aggregation for 3D Instance Segmentation](https://arxiv.org/abs/2108.02350) `segmentation`

  - [[Code](https://github.com/hustvl/HAIS)]

- [3DVG-Transformer: Relation Modeling for Visual Grounding on Point Clouds.](https://openaccess.thecvf.com/content/ICCV2021/papers/Zhao_3DVG-Transformer_Relation_Modeling_for_Visual_Grounding_on_Point_Clouds_ICCV_2021_paper.pdf) `3D Visual Grounding`

- [Perturbed Self-Distillation: Weakly Supervised Large-Scale Point Cloud

Semantic Segmentation.](https://openaccess.thecvf.com/content/ICCV2021/papers/Zhang_Perturbed_Self-Distillation_Weakly_Supervised_Large-Scale_Point_Cloud_Semantic_Segmentation_ICCV_2021_paper.pdf) `segmentation`

- [TempNet: Online Semantic Segmentation on Large-scale Point Cloud Series.](https://openaccess.thecvf.com/content/ICCV2021/papers/Zhou_TempNet_Online_Semantic_Segmentation_on_Large-Scale_Point_Cloud_Series_ICCV_2021_paper.pdf) `segmentation`

- [Robustness Certification for Point Cloud Models.](https://openaccess.thecvf.com/content/ICCV2021/papers/Lorenz_Robustness_Certification_for_Point_Cloud_Models_ICCV_2021_paper.pdf) `robustness`

  - [[Code](https://github.com/eth-sri/3dcertify)]

- [Shape Self-Correction for Unsupervised Point Cloud Understanding.](https://openaccess.thecvf.com/content/ICCV2021/papers/Chen_Shape_Self-Correction_for_Unsupervised_Point_Cloud_Understanding_ICCV_2021_paper.pdf) `Unsupervised learning`

- [Pyramid Point Cloud Transformer for Large-Scale Place Recognition.](https://openaccess.thecvf.com/content/ICCV2021/papers/Hui_Pyramid_Point_Cloud_Transformer_for_Large-Scale_Place_Recognition_ICCV_2021_paper.pdf) `Place_Recognition`

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

- [Geometry-Aware Self-Training for Unsupervised Domain Adaptation on Object Point Clouds.](https://openaccess.thecvf.com/content/ICCV2021/papers/Zou_Geometry-Aware_Self-Training_for_Unsupervised_Domain_Adaptation_on_Object_Point_Clouds_ICCV_2021_paper.pdf) `Domain Adaptation`

  - [[Code](https://github.com/zou-longkun/GAST)]

- [Differentiable Convolution Search for Point Cloud Processing.](https://openaccess.thecvf.com/content/ICCV2021/papers/Nie_Differentiable_Convolution_Search_for_Point_Cloud_Processing_ICCV_2021_paper.pdf) `NAS`

- [Learning Inner-group Relations on Point Clouds.](https://openaccess.thecvf.com/content/ICCV2021/papers/Ran_Learning_Inner-Group_Relations_on_Point_Clouds_ICCV_2021_paper.pdf) `classification`

  - [[Code](https://github.com/hancyran/RPNet-Point-Clouds)]

- [Point-Based Modeling of Human Clothing.](https://openaccess.thecvf.com/content/ICCV2021/papers/Zakharkin_Point-Based_Modeling_of_Human_Clothing_ICCV_2021_paper.pdf) 

  - [[Code](https://github.com/saic-vul/point_based_clothing)]

- [Cloud Transformers: A Universal Approach To Point Cloud Processing Tasks.](https://arxiv.org/pdf/2007.11679.pdf) `classification`

  - [[Code](https://github.com/saic-vul/cloud_transformers)]