zhanxinrui

zhanxinrui's Stars

• raulmur/ORB_SLAM2

  Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

  Language:C++9.5k3729674.7k

• IntelRealSense/librealsense

  Intel® RealSense™ SDK

  Language:C++7.7k2889.6k4.8k

• gaoxiang12/slambook

  Language:C++7k2722723.3k

• nianticlabs/monodepth2

  [ICCV 2019] Monocular depth estimation from a single image

  Language:Jupyter Notebook4.2k68484963

• orpatashnik/StyleCLIP

  Official Implementation for "StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery" (ICCV 2021 Oral)

  Language:HTML4k74118563

• MichaelGrupp/evo

  Python package for the evaluation of odometry and SLAM

  Language:Python3.5k50416758

• mapillary/OpenSfM

  Open source Structure-from-Motion pipeline

  Language:Python3.4k147657862

• tum-vision/lsd_slam

  LSD-SLAM

  Language:C++2.6k1933261.2k

• JakobEngel/dso

  Direct Sparse Odometry

  Language:C++2.3k115233911

• uzh-rpg/rpg_svo

  Semi-direct Visual Odometry

  Language:C++2.1k166260862

• tinghuiz/SfMLearner

  An unsupervised learning framework for depth and ego-motion estimation from monocular videos

  Language:Jupyter Notebook2k78145558

• luigifreda/pyslam

  pySLAM is a visual SLAM pipeline in Python for monocular, stereo and RGBD cameras. It supports many modern local and global features, different loop-closing methods, a volumetric reconstruction pipeline, and depth prediction models.

  Language:Python2k44104347

• princeton-vl/DROID-SLAM

  Language:Python1.8k42126305

• cvg/pixel-perfect-sfm

  Pixel-Perfect Structure-from-Motion with Featuremetric Refinement (ICCV 2021, Best Student Paper Award)

  Language:C++1.3k49113140

• gradslam/gradslam

  gradslam is an open source differentiable dense SLAM library for PyTorch

  Language:Python1.3k4738159

• yuval-alaluf/restyle-encoder

  Official Implementation for "ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement" (ICCV 2021) https://arxiv.org/abs/2104.02699

  Language:Python1k1880156

• ClementPinard/SfmLearner-Pytorch

  Pytorch version of SfmLearner from Tinghui Zhou et al.

  Language:Python1k26142227

• facebookresearch/co3d

  Tooling for the Common Objects In 3D dataset.

  Language:Python964838376

• devendrachaplot/Neural-SLAM

  Pytorch code for ICLR-20 Paper "Learning to Explore using Active Neural SLAM"

  Language:Python7682367144

• PeterWang512/GANSketching

  Sketch Your Own GAN: Customizing a GAN model with hand-drawn sketches.

  Language:Python711212695

• tum-vision/LDSO

  DSO with SIM(3) pose graph optimization and loop closure

  Language:C++6733866236

• POSTECH-CVLab/SCNeRF

  [ICCV21] Self-Calibrating Neural Radiance Fields

  Language:Python467162445

• aleksandrkim61/EagerMOT

  Official code for "EagerMOT: 3D Multi-Object Tracking via Sensor Fusion" [ICRA 2021]

  Language:Python405103578

• felixchenfy/Monocular-Visual-Odometry

  A simple monocular visual odometry (part of vSLAM) by ORB keypoints with initialization, tracking, local map and bundle adjustment. (WARNING: Hi, I'm sorry that this project is tuned for course demo, not for real world applications !!!)

  Language:C++403111491

• skyhehe123/VoxelNet-pytorch

  Language:Python3248985

• weixk2015/DeepSFM

  This is a PyTorch implementation of the ECCV2020 paper "DeepSFM: Structure From Motion Via Deep Bundle Adjustment".

  Language:Python32191745

• mihaidusmanu/local-feature-refinement

  Multi-View Optimization of Local Feature Geometry

  Language:Python22612824

• IsaacGuan/PointNet-Plane-Detection

  A 3D plane detection approach using PointNet

  Language:Python9951325

• jingedawang/FeatureMethod

  A demo for visual odometry in feature method using OpenCV.

  Language:Makefile723533

• umd-fire-coml/2020-3D-Object-Detection

  The purpose of this research is to do 3D object detection from a photo using machine learning. The goal is a working model that can detect multiple 3D objects and provide their dimensions and orientation given a photo. There are many ways to implement this, but this project uses center-based 3D object detection and tracking, where the model predicts the physical, three-dimensional center of detected objects, which is regressed to predict the dimensions and orientation of the object.

  Language:Jupyter Notebook13161