amonszpart

RAPter

RAPter: Rebuilding Man-made Scenes with Regular Arrangements of Planes, SIGGRAPH 2015

iMapper

iMapper: Interaction-guided Scene Mapping from Monocular Videos

SMASH

SMASH: Physics-guided Reconstruction of Collisions from Videos, SIGGRAPH Asia 2016

KinfuSuperRes

intrinsic

QCQPcpp

QCQP abstraction, with interface to Mosek

SegmentFH

C++ Wrapper for the super-pixelisation library from [Felzenszwalb and Huttenlocher 2004] from http://cs.brown.edu/~pff/segment/

3D_Pose_Estimation_CVPR2016

amonszpart.github.io

depth-hints

Depth Hints are complementary depth suggestions which improve monocular depth estimation algorithms trained from stereo pairs

footprints

Estimation of the visible and hidden traversable space from a single color image – CVPR 2020

Ansible

Ansible roles

apr

deepcut-cnn

CNN architecture for articulated human pose estimation

deeppose

DeepPose implementation by Chainer

geometry-tools

imusim

IMUSim - see http://www.imusim.org/

kornia

Open Source Differentiable Computer Vision Library for PyTorch

LargeScaleNeRFPytorch

1. Non-official implementation of Block-NeRF and Mega-NeRF in Pytorch. 2. Train your large-scale NeRF in the wild. 3. Weekly classified NeRF literature.

Lifting-from-the-Deep-release

Implementation of "Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image"

MCGraph

Multi-criteria graph representation for 3D scene-understanding

nerf

Code release for NeRF (Neural Radiance Fields)

OpenLeap

An initiative for an open source driver for the Leap Motion sensor.

pycolmap

Python bindings for COLMAP

pye57

Read and write e57 point clouds from Python

RAPterDeps

globOptDependencies

scisim

A 2D and 3D rigid body simulation framework with a focus on preserving core physical properties.

spatial-transformer-tensorflow

Spatial Transformer Networks with Affine, Projective and Elastic Transformations in Tensorflow

Technique-iOS

A simple implementation of SCNTechnique

vowpal_wabbit

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.