Structure from motion (SFM) definition
Estimates a scene's 3D structure from a collection of 2D photographs.
Structure from motion vs Photogrammetry
Unlike photogrammetry, the structure from motion approach does not require prior knowledge of 3D position, camera orientation, or control point information. A least square bundle adjustment technique aligns photos and produces a sparse point cloud reflecting the most prominent features in the images.
Resources (open source)
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Open source Structure from Motion pipeline
neural-networks depth-prediction self-supervised-learning unsupervised-learning visual-odometry
Bundler Structure from Motion Toolkit
3d-reconstruction 3d-vision bundle-adjustment computer-vision computer-vision-tools
depth disparity kitti unsupervised
augmented-reality awesome-list slam visual-inertial visual-odometry
depth-estimation kitti nyuv2-dataset sc-sfmlearner visual-odometry
depth-estimation eccv2020 extract-superpixel indoor nyuv2 pose-estimation scannet self-supervised unsupervised-learning
Robust SFM with Little Image Overlap
Usual Structure-from-Motion (SFM) techniques require at least trifocaloverlaps to calibrate cameras and reconstruct a scene. We consider herescenariOS of reduced image sets with little overlap, possibly...
monocular-depth pose-estimation self-supervised-learning
Deep Interpretable Non Rigid Structure from Motion
All current non-rigid structure from motion (NRSFM) algorithms are limitedwith respect to: (i) the number of images, and (ii) the type of shapevariability they can handle. This has hampered the practical...
2 months ago
Double precision SIMD oriented Fast Mersenne Twister
State Frequency Memory Recurrent Neural Networks
Modeling temporal sequences plays a fundamental role in various modern applications and has drawn more and more attentions in the machine learning community. Among those efforts on improving the capability...
3d-reconstruction bundle-adjustment bundler-sfm cvpr-2017 disambiguation image-based-modeling multiview-stereo multiview-triangulation point-cloud
brightness-calibration computer-vision neural-networks depth-estimation endoscopy monodepth pose-estimation self-supervision
Tool kit for doing PSF photometry
A harvester for twitter content as part of Social Feed Manager.
Distributed and Graph-Based Structure-from-Motion Library
MCMC 2D surface brightness fitting for quasar host galaxies
Fortran 2003 interface to the dSFMT pseudo-random number generator
Towards Continual, Online, Unsupervised Depth
Although depth extraction with passive sensors has seen remarkable improvement with deep learning, these approaches may fail to obtain correct depth if they are exposed to environments not observed during...
A summary of the paper "Trajectory Space NRSFM Revisited"
Code accompanying Tooley et al. (2020), Associations between Neighborhood SES & Functional Brain Development. https://doi.org/10.1093/cercor/bhz066
This is a Tensorflow implementation of DeepSFM.
VoxelNet: End to End Learning for Point Cloud Based 3D Object Detection
Accurate detection of objects in 3D point clouds is a central problem in manyapplications, such as autonomous navigation, housekeeping robots, andaugmented/virtual reality. To interface a highly sparse...conference Frustum PointNets for 3D Object Detection from RGB D Data
In this work, we study 3D object detection from RGB-D data in both indoor andoutdoor scenes. While previous methods focus on images or 3D voxels, oftenobscuring natural 3D patterns and invariances of 3D...conference PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Point cloud is an important type of geometric data structure. Due to itsirregular format, most researchers transform such data to regular 3D voxelgrids or collections of images. This, however, renders...conference PCPNET: Learning Local Shape Properties from Raw Point Clouds
In this paper, we propose PCPNet, a deep-learning based approach forestimating local 3D shape properties in point clouds. In contrast to themajority of prior techniques that concentrate on global or mid-levelattributes,...
Statistical finite elements with Markov chain Monte Carlo