Salzburg, Austria

Mihai Bujanca

Expert
@mihaibujanca

Computer Vision & Machine Learning

dynamicfusion. Implementation of Newcombe et al. CVPR 2015 DynamicFusion paper

413

slambench3. C++

50

awesome_3DReconstruction_list. A curated list of papers & ressources linked to 3D reconstruction from images.

8

awesome-computer-vision. A curated list of awesome computer vision resources

5

V360. Video 3D on accelerometer, with panframe SDK

3

KinectFusionLib. Implementation of the KinectFusion approach in modern C++14 and CUDA

3

salz21. Python

2

Nathans_Augmented_Reality. Augmented Reality Game Demo

2

ORB_SLAM3. ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM

2

flame. FLaME: Fast Lightweight Mesh Estimation

1

SceneGraphFusion. C++

1

open_vins. An open source platform for visual-inertial navigation research.

1

Fast_RNRR. Source code for the paper "Quasi-Newton Solver for Robust Non-Rigid Registration" (CVPR2020 Oral).

1

InfiniTAM. A Framework for the Volumetric Integration of Depth Images

1

neuralrgbd. Neural RGB→D Sensing: Per-pixel depth and its uncertainty estimation from a monocular RGB video

1

yolact_edge. The first competitive instance segmentation approach that runs on small edge devices at real-time speeds.

1

refusion. ReFusion: 3D Reconstruction in Dynamic Environments for RGB-D Cameras Exploiting Residuals

1

awesome-orb-slam. A list of resources related to ORB-SLAM

1

neuralvolumes. Training and Evaluation Code for Neural Volumes

1

slambench2. SLAM performance evaluation framework

1

sms2ssh. Ssh into a machine by sms.

1

Tutorials. [Work in progress] Code for a couple of tutorials for Kinect C++ SDK, Wiiuse, and various other AR-related topics.

1

Opt. Opt DSL

1

soundGR. C++

1

ElasticReconstruction. Code for RGBD reconstruction. Modified from the code from http://redwood-data.org/indoor/pipeline.html

1

crfasrnn. This repository contains the source code for the semantic image segmentation method described in the ICCV 2015 paper: Conditional Random Fields as Recurrent Neural Networks. http://crfasrnn.torr.vision/

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