EOLab

EOLab's Stars

• microsoft/DeepSpeed

  DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

  Language:Python33.5k3402.6k3.9k

• ctgk/PRML

  PRML algorithms implemented in Python

  Language:Jupyter Notebook11.3k419243.3k

• facebookresearch/pytorch3d

  PyTorch3D is FAIR's library of reusable components for deep learning with 3D data

  Language:Python8.4k1481.5k1.3k

• google/neural-tangents

  Fast and Easy Infinite Neural Networks in Python

  Language:Jupyter Notebook2.2k63152228

• MIT-SPARK/TEASER-plusplus

  A fast and robust point cloud registration library

  Language:C++1.7k46147331

• PRBonn/OverlapNet

  OverlapNet - Loop Closing for 3D LiDAR-based SLAM (chen2020rss)

  Language:Python6362729114

• VincentCheungM/Run_based_segmentation

  An ongoing implementation ros node on `fast segmentation of 3d point clouds: a paradigm`...

  Language:C++3811123121

• WangYueFt/dcp

  Language:Python345123190

• kgl-prml/Contrastive-Adaptation-Network-for-Unsupervised-Domain-Adaptation

  pytorch implementation for Contrastive Adaptation Network

  Language:Python32061858

• KovenYu/MAR

  Pytorch code for our CVPR'19 (oral) work: Unsupervised person re-identification by soft multilabel learning

  Language:Python314113884

• papagina/RotationContinuity

  Coder for "On the Continuity of Rotation Representations"

  Language:Python313121753

• alexstaravoitau/KITTI-Dataset

  Visualising LIDAR data from KITTI dataset.

  Language:Jupyter Notebook298111392

• taki0112/Tensorflow2-Cookbook

  Simple Tensorflow 2.x Cookbook for easy-to-use

  Language:Python26422152

• alinlab/L2T-ww

  Learning What and Where to Transfer (ICML 2019)

  Language:Python25171047

• yewzijian/3DFeatNet

  3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration

  Language:Python219192046

• WangYueFt/prnet

  prnet

  Language:Python11471429

• SRainGit/CAE-LO

  CAE-LO: LiDAR Odometry Leveraging Fully Unsupervised Convolutional Auto-Encoder for Interest Point Detection and Feature Description

  Language:Python113111428

• MyeongJin-Kim/Learning-Texture-Invariant-Representation

  Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation, CVPR 2020

  Language:Python10541311

• vinits5/pcrnet_pytorch

  This is a pytorch implementation of PCRNet

  Language:Python7341713

• Ha0Tang/C2GAN

  [ACM MM 2019 Oral] Cycle In Cycle Generative Adversarial Networks for Keypoint-Guided Image Generation

  Language:Python695135

• pmorerio/minimal-entropy-correlation-alignment

  Code for the paper "Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation", ICLR 2018

  Language:Python624517

• feiyuhuahuo/create-a-hdf5-data-set-for-deep-learning

  create your own data set with python library h5py and a simple example for image recognition

  Language:Python451118

• snudatalab/KegNet

  Knowledge Extraction with No Observable Data (NeurIPS 2019)

  Language:Python424511

• wentaoyuan/it-net

  Implementation of Iterative Transformer Network for 3D Point Cloud

  Language:Python40625

• vinits5/pointnet-registration-framework

  Code for the paper "One Framework to Register Them All: PointNet Encoding for Point Cloud Alignment"

  Language:Python357

• Xiewp/PFAN

  Code for CVPR-2019 paper "Progressive Feature Alignment for Unsupervised Domain Adaptation"

  Language:Python30205

• LavieLuo/DRMEA

  Pytorch code for “Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment ” (DRMEA) (AAAI 2020).

  Language:Python29107

• zawlin/6d_rot

  Language:Jupyter Notebook29203

• NNU-GISA/FoldingNet

  Organized code for the paper "FoldingNet: Point Cloud Auto-encoder via Deep Grid Deformation" (CVPR 2018).

  Language:Python101

• adioshun/links

  추천링크

  6101