Search Results for "3d linux" - Page 2
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Showing 42 open source projects for "3d linux"
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Semantic Segmentation Editor
Web labeling tool for bitmap images and point clouds
A web-based labeling tool for creating AI training data sets (2D and 3D). The tool has been developed in the context of autonomous driving research. It supports images (.jpg or .png) and point clouds (.pcd). It is a Meteor app developed with React, Paper.js, and three.js. -
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OpenPose
Real-time multi-person keypoint detection library for body, face, etc.
OpenPose has represented the first real-time multi-person system to jointly detect human body, hand, facial, and foot keypoints (in total 135 keypoints) on single images. It is authored by Ginés Hidalgo, Zhe Cao, Tomas Simon, Shih-En Wei, Yaadhav Raaj, Hanbyul Joo, and Yaser Sheikh. It is maintained by Ginés Hidalgo and Yaadhav Raaj. OpenPose would not be possible without the CMU Panoptic Studio dataset. We would also like to thank all the people who has helped OpenPose in any way. 15, 18 or... -
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gradslam
gradslam is an open source differentiable dense SLAM library
gradslam is an open-source framework providing differentiable building blocks for simultaneous localization and mapping (SLAM) systems. We enable the usage of dense SLAM subsystems from the comfort of PyTorch. The question of “representation” is central in the context of dense simultaneous localization and mapping (SLAM). Newer learning-based approaches have the potential to leverage data or task performance to directly inform the choice of representation. However, learning representations... -
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MMSkeleton
A OpenMMLAB toolbox for human pose estimation, skeleton-based action
MMSkeleton is an open-source toolbox for skeleton-based human understanding. It is a part of the open-mmlab project in the charge of Multimedia Laboratory, CUHK. MMSkeleton is developed on our research project ST-GCN. MMSkeleton provides a flexible framework for organizing codes and projects systematically, with the ability to extend to various tasks and scale up to complex deep models. MMSkeleton addresses to multiple tasks in human understanding. Build a custom skeleton-based dataset.... -
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NiftyNet
An open-source convolutional neural networks platform for research
An open-source convolutional neural networks platform for medical image analysis and image-guided therapy. NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging... -
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TenorSpace.js
Neural network 3D visualization framework
TensorSpace is a neural network 3D visualization framework built using TensorFlow.js, Three.js and Tween.js. TensorSpace provides Keras-like APIs to build deep learning layers, load pre-trained models, and generate a 3D visualization in the browser. From TensorSpace, it is intuitive to learn what the model structure is, how the model is trained and how the model predicts the results based on the intermediate information. After preprocessing the model, TensorSpace supports the visualization... -
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3D ResNets for Action Recognition
3D ResNets for Action Recognition (CVPR 2018)
We uploaded the pretrained models described in this paper including ResNet-50 pretrained on the combined dataset with Kinetics-700 and Moments in Time. We significantly updated our scripts. If you want to use older versions to reproduce our CVPR2018 paper, you should use the scripts in the CVPR2018 branch. -
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The Teachingbox uses advanced machine learning techniques to relieve developers from the programming of hand-crafted sophisticated behaviors of autonomous agents (such as robots, game players etc...) In the current status we have implemented a well founded reinforcement learning core in Java with many popular usecases, environments, policies and learners. Obtaining the teachingbox: FOR USERS: If you want to download the latest releases, please visit:...
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Five video classification methods
Code that accompanies my blog post outlining five video classification
Classifying video presents unique challenges for machine learning models. As I’ve covered in my previous posts, video has the added (and interesting) property of temporal features in addition to the spatial features present in 2D images. While this additional information provides us more to work with, it also requires different network architectures and, often, adds larger memory and computational demands.We won’t use any optical flow images. This reduces model complexity, training time, and... -
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Lip Reading
Cross Audio-Visual Recognition using 3D Architectures
The input pipeline must be prepared by the users. This code is aimed to provide the implementation for Coupled 3D Convolutional Neural Networks for audio-visual matching. Lip-reading can be a specific application for this work. Audio-visual recognition (AVR) has been considered as a solution for speech recognition tasks when the audio is corrupted, as well as a visual recognition method used for speaker verification in multi-speaker scenarios. The approach of AVR systems is to leverage the... -
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Keras.js
Run Keras models in the browser, with GPU support using WebGL
Run Keras models in the browser, with GPU support provided by WebGL 2. Models can be run in Node.js as well, but only in CPU mode. Because Keras abstracts away a number of frameworks as backends, the models can be trained in any backend, including TensorFlow, CNTK, etc. Check out the demos/ directory for real examples running Keras.js in VueJS. Library version compatibility, Keras 2.1.2. -
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Automatic cell lineage reconstruction
Automatic segmentation and tracking for 3D time-lapse microscopy
From Amat et al., Nature Methods, 2014*: "The comprehensive reconstruction of cell lineages in complex multicellular organisms is a central goal of developmental biology. We present an open-source computational framework for segmentation and tracking of cell nuclei with high accuracy and speed. We demonstrate its (1) generality, by reconstructing cell lineages in four-dimensional, terabyte-sized image data of fruit-fly, zebrafish and mouse embryos, acquired with three different types of... -
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Customizable software to smoothly fit non-linear, high-dimensional data. SDK in C with C++ wrappers, plus demo applications (all under LGPL). Versions under Windows and Linux already operational. Further progress depends on your imagination!
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Black Hole Cortex
Sphere surface layers of visual cortex approach maximum info density
Near the surface (even horizon) of a black hole, there is maximum information density in units of squared plancks (and some translation to qubits). Similarly, our imagination is the set of all possible things we can draw onto our most dense layer of visual cortex in electricity patterns. Bigger layers have more neurons to handle those possibilities. A Black Hole Cortex is a kind of visual cortex that has density of neuron layers similar to density at various radius from a black hole. What we... -
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With miao3d you can train a specific Gaussian Markov Random Field (GMRF) that then can be used to estimate a depthmap ("3D"), given an image ("2D"). A GUI allows inspection of the image + depthmap.
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SmartMap
SmartMap is an easy desktop random world creator.
SmartMap (C# cross-platform) is a procedural style world-map creation utility or "Desktop World." A simple scene manager is included using plugin style building blocks and object pathfinding. Also included is a 2D world editor with graphical features. SmartMap is currently built in conjunction with the Axiom 3D rendering engine.
