nerfmm
SuperGluePretrainedNetwork
| nerfmm | SuperGluePretrainedNetwork | |
|---|---|---|
| 2 | 5 | |
| 539 | 3,036 | |
| 0.7% | 4.3% | |
| 2.0 | 0.0 | |
| 9 months ago | over 1 year ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
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nerfmm
SuperGluePretrainedNetwork
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SuperGlue is a CVPR2022 research project done at Magicleap for pose estimation in real-world environments. Check out the tool link in the comments
Code: https://github.com/magicleap/SuperGluePretrainedNetwork
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Advances in SLAM since 2016
This basically includes a deep learning based approach to do keypoint detection, and match them across image frames. This includes papers like SuperPoint, Superglue, and more. There is also a way to do dense matching with neural networks.
- [D] Solo machine learning engineer woes
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How to train a CNN for a map localization task?
Feature matching is the way to go imo. Try out OpenCV's inbuilt feature matching methods like SIFT and FLANN. If the performance is poor, you can even try out CNN aided matching algos like SuperGlue Link (CVPR2020)
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What is the SOTA for feature extraction / description / matching ?
SIFT and brute force matching is your best bet in classical computer vision if you're unconcerned with runtime. There are methods from deep learning that can perform better, somewhat domain dependent. Check out superpoint and superglue from magic leap. https://github.com/magicleap/SuperGluePretrainedNetwork
What are some alternatives?
3d-photo-inpainting - [CVPR 2020] 3D Photography using Context-aware Layered Depth Inpainting
LoFTR - Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021, T-PAMI 2022
Hierarchical-Localization - Visual localization made easy with hloc
ORB_SLAM3 - ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM
pi-GAN-pytorch - Implementation of π-GAN, for 3d-aware image synthesis, in Pytorch
dgl - Python package built to ease deep learning on graph, on top of existing DL frameworks.
lightweight-human-pose-estimation.pytorch - Fast and accurate human pose estimation in PyTorch. Contains implementation of "Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose" paper.
torchdrug - A powerful and flexible machine learning platform for drug discovery
multinerf - A Code Release for Mip-NeRF 360, Ref-NeRF, and RawNeRF
DeepLabCut - Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
AlphaPose - Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System
open_vins - An open source platform for visual-inertial navigation research.