newtonian

Object dynamics predictor

This Lua project predicts the dynamics of objects in static images by understanding Newtonian physics

GitHub

32 stars
6 watching
6 forks
Language: Lua
last commit: over 8 years ago
Linked from 1 awesome list


Backlinks from these awesome lists:

Related projects:

Repository Description Stars
junyanz/realismcnn Predicts and improves visual realism in composite images using deep learning techniques 64
oniietzschan/bump-3dpd A Lua library for fast and simple axis-aligned 3D collision detection 77
rozenmad/menori A Lua-based 3D rendering library using scene graph and glTF 2.0 support 162
clementfarabet/manifold Manages and transforms high-dimensional data into lower-dimensional representations using various algorithms 141
sheffieldml/multigp Software for modeling and prediction with multiple output Gaussian processes 48
rozumden/defmo A deep learning framework for deblurring and recovering the shape of fast-moving objects from blurred images 171
aweptimum/strike An open-source 2D collision detection library using the Separating-Axis Theorem for Lua 28
lz118/deep-correlation-network Develops a deep neural network model for detecting salient objects in RGBT images using correlation information from other colors. 13
vonfeng/deepmove A PyTorch-based implementation of a predictive model for human mobility patterns using attention mechanisms and recurrent neural networks. 149
denissimon/prediction-builder A PHP library that builds predictions using linear regression. 111
azoyan/shakedetectorlua A Lua port of the shake detection library for detecting shakes in games using accelerometer data and delta-time between update cycles. 5
spacewander/lua-resty-mime-sniff This Lua library detects and matches the MIME type of given data in a web application 11
clementfarabet/ipam-tutorials Hands-on tutorials and code examples for implementing supervised and unsupervised learning algorithms in Lua using the Torch7 deep learning framework. 130
atomistic-machine-learning/dtnn An open-source Python framework for developing machine learning models to predict quantum-mechanical observables of molecular systems. 78
atomistic-machine-learning/schnetpack A toolbox for training and applying deep neural networks to predict atomistic properties of molecules and materials 795