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This repository consist of python code, input and output images for generating a point cloud obtained from a depth map image of a stereo image pair. Point cloud of an object allows a robot to determine coordinates of every point of that object with respect to world coordinates. It is extremely useful in humanoid robots.
Implementation of batch normalization to avoid overfitting
Batch normalization was introduced in Sergey Ioffe's and Christian Szegedy's 2015 paper Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. The idea is that, instead of just normalizing the inputs to the network, we normalize the inputs to layers within the network. It's called "batch" normalization because during training, we normalize each layer's inputs by using the mean and variance of the values in the current mini-batch.
Python code for the fast bilateral solver
Pytorch implementation of NIPS 2017 paper "Modulating early visual processing by language"
Convolutional Spatial Propagation Network
Unofficial Faster PyTorch implementation of Convolutional Spatial Propagation Network
Code and data for paper "Deep Photo Style Transfer": https://arxiv.org/abs/1703.07511
Deep Depth Completion of a Single RGB-D Image
Deep Surface Normal Guided Depth Prediction for Outdoor Scene from Sparse LiDAR Data and Single Color Image
Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation
ITSC 2019 | This is the accompanying code repository for our paper "DFuseNet: Deep Fusion of RGB and Sparse Depth Information for Image Guided Dense Depth Completion" | PyTorch, Python 3
Pytorch implementation of the several Deep Stereo Matching Network
GCNet: End-to-End Learning of Geometry and Context for Deep Stereo Regression (Tensorflow Implementation)
Intensity-based_Lidar_Camera_Calibration
(Eyebeam #5 of 13) Records Kinect depth maps as 8-bit grayscale images. Use [ https://github.com/N1ckFG/Kinect_justrecord_post ] to fix sync or [ https://github.com/N1ckFG/Pointcloud_Render ] to batch export OBJ files.
LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain
浙大开源的Lidar IMU标定工具,适配了自己的数据集。
Targetless Calibration of LiDAR-IMU System Based on Continuous-time Batch Estimation
Single Image Depth Estimation with Feature Pyramid Network
(Eyebeam #10 of 13) Convert a grayscale depth map image to a point cloud; save in formats including OBJ, PLY, ASC.
official implementation of "Revisiting Single Image Depth Estimation: Toward Higher Resolution Maps with Accurate Object Boundaries"
ROS Bridge Driver for Carla Simulator package : https://github.com/carla-simulator/carla
Code Release for "Static and Dynamic Guidance Filtering" CVPR 2015.
ICRA 2019 "Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera"
An unsupervised learning framework for depth and ego-motion estimation from monocular videos
transform 2D rgb and depth image to 3D point cloud with color.
opencv solve的算法仓库
Implementation of "Stereo and LiDAR Fusion using Stereo Matching Network with Conditional Cost Volume Normalization"
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.