Awesome
README
Updated: 4th October 2018.
Computer Vision and Intelligence Group, IIT Madras
<img src=/avatar.png width=400 height=200></img>
Blog: iitmcvg.github.io
This repository contains content that we use for CNN SLAM. Original paper
Contributors
- Varun Sundar
- Aditya S
- Aaaryaan
Table of Contents
Experiments
- Heterogenous graphs; convert every CPU op into a compute graph and note performance with placement.
- Stereo matching methods and GPU optimisation.
- CPU efficient object detectors and depth estimators.
- Indoor optimised depth estimation (monocular.)
To Do
- Complete camera pose estimation.
- Monocular depth methods library.
- Freeze graphs for inference.
- Sample runs.
- Global Graph Optimisation.