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occuseg

This is the official code repository for OccuSeg, a state-of-the-art method for accurate joint 3D semantic and instance segmentation.

open_ipcl

official repository for the Instance Prototype Contrastive Learning (IPCL)

openfl

An open framework for Federated Learning.

openpoints

OpenPoints: a library for easily reproducing point-based methods for point cloud understanding. The engine for [PointNeXt](https://arxiv.org/abs/2206.04670)

openseg.pytorch

The official Pytorch implementation of OCNet series and SegFix.

paconv

(CVPR 2021) PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds

paddlefl

Federated Deep Learning in PaddlePaddle

panoptic-polarnet

Implementation for Panoptic-PolarNet (CVPR 2021)

parametric-contrastive-learning

Parametric Contrastive Learning (ICCV2021)

passl

PASSL包含 SimCLR，MoCo v1/v2，BYOL，CLIP，PixPro，simsiam, SwAV, BEiT，MAE 等图像自监督算法以及 Vision Transformer，DEiT，Swin Transformer，CvT，T2T-ViT，MLP-Mixer，XCiT，ConvNeXt，PVTv2 等基础视觉算法

patch-fool

[ICLR 2022] "Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?" by Yonggan Fu, Shunyao Zhang, Shang Wu, Cheng Wan, Yingyan Lin

pcl

PyTorch code for "Prototypical Contrastive Learning of Unsupervised Representations"

pfcnn

Code for the paper "PFCNN: Convolutional Neural Networks on 3D Surfaces Using Parallel Frames" (CVPR 2020).

pflm

Privacy-preserving federated learning is distributed machine learning where multiple collaborators train a model through protected gradients. To achieve robustness to users dropping out, existing practical privacy-preserving federated learning schemes are based on (t, N)-threshold secret sharing. Such schemes rely on a strong assumption to guarantee security: the threshold t must be greater than half of the number of users. The assumption is so rigorous that in some scenarios the schemes may not be appropriate. Motivated by the issue, we first introduce membership proof for federated learning, which leverages cryptographic accumulators to generate membership proofs by accumulating users IDs. The proofs are issued in a public blockchain for users to verify. With membership proof, we propose a privacy-preserving federated learning scheme called PFLM. PFLM releases the assumption of threshold while maintaining the security guarantees. Additionally, we design a result verification algorithm based on a variant of ElGamal encryption to verify the correctness of aggregated results from the cloud server. The verification algorithm is integrated into PFLM as a part. Security analysis in a random oracle model shows that PFLM guarantees privacy against active adversaries. The implementation of PFLM and experiments demonstrate the performance of PFLM in terms of computation and communication.

pixel-nerf

PixelNeRF Official Repository

pnal

Learning with Noisy Labels for Robust Point Cloud Segmentation (ICCV2021 Oral)

pnp-3d

PnP-3D: A Plug-and-Play for 3D Point Clouds (TPAMI 2021)

point-bert

[CVPR 2022] Pre-Training 3D Point Cloud Transformers with Masked Point Modeling

point-clouds-visualization

visualization点云可视化(open3D, mayavi等)

point-mae

point-transformer

This is an unofficial implementation of the Point Transformer paper.

pointaugment

Code for PointAugment: an Auto-Augmentation Framework for Point Cloud Classification, CVPR 2020 (Oral)

pointclip

[CVPR 2022] PointCLIP: Point Cloud Understanding by CLIP

pointcloud_tutorial

This is a fundamental manual for getting started with Point Cloud, covering basic knowledge of point cloud, point cloud file format, CloudCompare and MeshLab software instructions, PCL library algorithm introduction and other algorithms supplementary.

pointcontrast

Code for paper <PointContrast: Unsupervised Pretraining for 3D Point Cloud Understanding>

pointmixer

pointmixup

Implementation for paper "PointMixup: Augmentation for Point Cloud". Accepted to ECCV 2020 as spotlight presentation

pointmlp-pytorch

[ICLR 2022 poster] Official PyTorch implementation of "Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework"

pointnerf

Point-NeRF: Point-based Neural Radiance Fields

pointnet

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation