Implementation of Monocular Direct Sparse Localization in a Prior 3D Surfel Map (DSL)

Related tags

Deep Learningdsl
Overview

DSL

Project page: https://sites.google.com/view/dsl-ram-lab/

Monocular Direct Sparse Localization in a Prior 3D Surfel Map

Authors: Haoyang Ye, Huaiyang Huang, and Ming Liu from RAM-LAB.

Paper and Video

Related publications:

@inproceedings{ye2020monocular,
  title={Monocular direct sparse localization in a prior 3d surfel map},
  author={Ye, Haoyang and Huang, Huaiyang and Liu, Ming},
  booktitle={2020 IEEE International Conference on Robotics and Automation (ICRA)},
  pages={8892--8898},
  year={2020},
  organization={IEEE}
}
@inproceedings{ye20213d,
  title={3D Surfel Map-Aided Visual Relocalization with Learned Descriptors},
  author={Ye, Haoyang and Huang, Huaiyang and Hutter, Marco and Sandy, Timothy and Liu, Ming},
  booktitle={2021 International Conference on Robotics and Automation (ICRA)},
  pages={5574-5581},
  year={2021},
  organization={IEEE}
}

Video: https://www.youtube.com/watch?v=LTihCBGcURo

Dependency

  1. Pangolin.
  2. CUDA.
  3. Ceres-solver.
  4. PCL, the default version accompanying by ROS.
  5. OpenCV, the default version accompanying by ROS.

Build

  1. git submodule update --init --recursive
  2. mkdir build && cd build
  3. cmake .. -DCMAKE_BUILD_TYPE=RelWithDebInfo
  4. make -j8

Example

The sample config file can be downloaded from this link.

To run the example:

[path_to_build]/src/dsl_main --path "[path_to_dataset]/left_pinhole"

Preparing Your Own Data

  1. Collect LiDAR and camera data.
  2. Build LiDAR map and obtain LiDAR poses (the poses are not necessary).
  3. Pre-process LiDAR map to make the [path_to_dataset]/*.pcd map file contains normal_x, normal_y, normal_z fields (downsample & normal estimation).
  4. Extract and undistort images into [path_to_dataset]/images.
  5. Set the first camera pose to initial_pose and other camera parameters in [path_to_dataset]/config.yaml.

Note

This implementation of DSL takes Ceres Solver as backend, which is different from the the implementation of the original paper with DSO-backend. This leads to different performance, i.e., speed and accuracy, compared to the reported results.

Credits

This work is inspired from several open-source projects, such as DSO, DSM, Elastic-Fusion, SuperPoint, DBoW2, NetVlad, LIO-mapping and etc.

Licence

The source code is released under GPL-3.0.

机器学习、深度学习、自然语言处理等人工智能基础知识总结。

说明 机器学习、深度学习、自然语言处理基础知识总结。 目前主要参考李航老师的《统计学习方法》一书,也有一些内容例如XGBoost、聚类、深度学习相关内容、NLP相关内容等是书中未提及的。

Peter 445 Dec 12, 2022
Simple converter for deploying Stable-Baselines3 model to TFLite and/or Coral

Running SB3 developed agents on TFLite or Coral Introduction I've been using Stable-Baselines3 to train agents against some custom Gyms, some of which

Gary Briggs 16 Oct 11, 2022
Python parser for DTED data.

DTED Parser This is a package written in pure python (with help from numpy) to parse and investigate Digital Terrain Elevation Data (DTED) files. This

Ben Bonenfant 12 Dec 18, 2022
This repo contains the pytorch implementation for Dynamic Concept Learner (accepted by ICLR 2021).

DCL-PyTorch Pytorch implementation for the Dynamic Concept Learner (DCL). More details can be found at the project page. Framework Grounding Physical

Zhenfang Chen 31 Jan 06, 2023
Efficient-GlobalPointer - Pytorch Efficient GlobalPointer

引言 感谢苏神带来的模型,原文地址:https://spaces.ac.cn/archives/8877 如何运行 对应模型EfficientGlobalPoi

powerycy 40 Dec 14, 2022
Wordle-solver - Wordle answer generation program in python

🟨 Wordle Solver 🟩 Wordle answer generation program in python ✔️ Requirements U

Dahyun Kang 4 May 28, 2022
Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs

Project Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs, https://arxiv.org/pdf/2111.01940.pdf. Authors Truong Son Hy

5 Jun 28, 2022
The official PyTorch code implementation of "Human Trajectory Prediction via Counterfactual Analysis" in ICCV 2021.

Human Trajectory Prediction via Counterfactual Analysis (CausalHTP) The official PyTorch code implementation of "Human Trajectory Prediction via Count

46 Dec 03, 2022
[CVPR 2021] Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach

Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach This is the repo to host the dataset TextSeg and code for TexRNe

SHI Lab 174 Dec 19, 2022
VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition

VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition Usage First, install PyTorch 1.7.1+, torchvision 0.8.2

40 Dec 12, 2022
Official implementation of our paper "Learning to Bootstrap for Combating Label Noise"

Learning to Bootstrap for Combating Label Noise This repo is the official implementation of our paper "Learning to Bootstrap for Combating Label Noise

21 Apr 09, 2022
《Single Image Reflection Removal Beyond Linearity》(CVPR 2019)

Single-Image-Reflection-Removal-Beyond-Linearity Paper Single Image Reflection Removal Beyond Linearity. Qiang Wen, Yinjie Tan, Jing Qin, Wenxi Liu, G

Qiang Wen 51 Jun 24, 2022
Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation

Photographic Image Synthesis with Cascaded Refinement Networks-Pytorch (https://arxiv.org/abs/1707.09405) This is a Pytorch implementation of cascaded

Soumya Tripathy 63 Mar 27, 2022
Source code for From Stars to Subgraphs

GNNAsKernel Official code for From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness Visualizations GNN-AK(+) GNN-AK(+) with Subgra

44 Dec 19, 2022
Nvidia Semantic Segmentation monorepo

Paper | YouTube | Cityscapes Score Pytorch implementation of our paper Hierarchical Multi-Scale Attention for Semantic Segmentation. Please refer to t

NVIDIA Corporation 1.6k Jan 04, 2023
Canonical Capsules: Unsupervised Capsules in Canonical Pose (NeurIPS 2021)

Canonical Capsules: Unsupervised Capsules in Canonical Pose (NeurIPS 2021) Introduction This is the official repository for the PyTorch implementation

165 Dec 07, 2022
A Deep Learning Framework for Neural Derivative Hedging

NNHedge NNHedge is a PyTorch based framework for Neural Derivative Hedging. The following repository was implemented to ease the experiments of our pa

GUIJIN SON 17 Nov 14, 2022
A deep learning based semantic search platform that computes similarity scores between provided query and documents

semanticsearch This is a deep learning based semantic search platform that computes similarity scores between provided query and documents. Documents

1 Nov 30, 2021
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

ENet in Caffe Execution times and hardware requirements Network 1024x512 1280x720 Parameters Model size (fp32) ENet 20.4 ms 32.9 ms 0.36 M 1.5 MB SegN

Timo Sämann 561 Jan 04, 2023
Model Zoo of BDD100K Dataset

Model Zoo of BDD100K Dataset

ETH VIS Group 200 Dec 27, 2022