A collection of educational notebooks on multi-view geometry and computer vision.

Overview

Binder

Multiview notebooks

This is a collection of educational notebooks on multi-view geometry and computer vision. Subjects covered in these notebooks include:

  • Camera calibration
  • Perspective projection
  • 3D point triangulation
  • Quaternions as 3D pose representation
  • Perspective-n-point (PnP) algorithm
  • Levenberg–Marquardt optimization
  • Epipolar geometry
  • Relative 2nd cam pose from stereo views w. fundamental matrix
  • Relative 2nd cam pose from stereo views w. homography
  • Bundle adjustment
  • Structure from motion

Note Notebook 5 is working but not as tidy as the rest (yet). This notebook covers the Faugeras method to infer relative pose from a homography.

How to run

The notebooks can be run in the browser by clicking the binder badge Binder. If one is interested in running the notebooks locally, I highly recommend using Docker as there is a dependency on g2opy and ipyvolume, which are challenging to install.

# Builds the environment 
docker build -t multiview_notebooks .

# Start a jupyter lab which can be opened in the browser
docker run -it --rm -p 8888:8888 multiview_notebooks jupyter-lab --ip=0.0.0.0 --port=8888

After starting the jupyter lab, the notebooks can be found in the home directory.
For the source of the Dockerfile, see this repository

Examples of visualizations

For more examples, see this video on youtube

Triangulation




Perspective n Point

Deep Compression for Dense Point Cloud Maps.

DEPOCO This repository implements the algorithms described in our paper Deep Compression for Dense Point Cloud Maps. How to get started (using Docker)

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Code for our NeurIPS 2021 paper: Sparsely Changing Latent States for Prediction and Planning in Partially Observable Domains

GateL0RD This is a lightweight PyTorch implementation of GateL0RD, our RNN presented in "Sparsely Changing Latent States for Prediction and Planning i

Autonomous Learning Group 16 Nov 03, 2022
Code for "Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue Generation". [AAAI 2021]

Graph Evolving Meta-Learning for Low-resource Medical Dialogue Generation Code to be further cleaned... This repo contains the code of the following p

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Open AI's Python library

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"Exploring Vision Transformers for Fine-grained Classification" at CVPRW FGVC8

FGVC8 Exploring Vision Transformers for Fine-grained Classification paper presented at the CVPR 2021, The Eight Workshop on Fine-Grained Visual Catego

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StrongSORT: Make DeepSORT Great Again

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Reproduces ResNet-V3 with pytorch

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In the AI for TSP competition we try to solve optimization problems using machine learning.

AI for TSP Competition Goal In the AI for TSP competition we try to solve optimization problems using machine learning. The competition will be hosted

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A supplementary code for Editable Neural Networks, an ICLR 2020 submission.

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Creating a custom CNN hypertunned architeture for the Fashion MNIST dataset with Python, Keras and Tensorflow.

custom-cnn-fashion-mnist Creating a custom CNN hypertunned architeture for the Fashion MNIST dataset with Python, Keras and Tensorflow. The following

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Inteligência artificial criada para realizar interação social com idosos.

IA SONIA 4.0 A SONIA foi inspirada no assistente mais famoso do mundo e muito bem conhecido JARVIS. Todo mundo algum dia ja sonhou em ter o seu própri

Vinícius Azevedo 2 Oct 21, 2021
AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation

AtlasNet [Project Page] [Paper] [Talk] AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation Thibault Groueix, Matthew Fisher, Vladimir

577 Dec 17, 2022
End-to-End Object Detection with Fully Convolutional Network

This project provides an implementation for "End-to-End Object Detection with Fully Convolutional Network" on PyTorch.

472 Dec 22, 2022
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

Image Super-Resolution (ISR) The goal of this project is to upscale and improve the quality of low resolution images. This project contains Keras impl

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This is a template for the Non-autoregressive Deep Learning-Based TTS model (in PyTorch).

Non-autoregressive Deep Learning-Based TTS Template This is a template for the Non-autoregressive TTS model. It contains Data Preprocessing Pipeline D

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The code repository for EMNLP 2021 paper "Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization".

Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization [Paper] accepted at the EMNLP 2021: Vision Guided Genera

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NVIDIA Deep Learning Examples for Tensor Cores

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Code for EmBERT, a transformer model for embodied, language-guided visual task completion.

Code for EmBERT, a transformer model for embodied, language-guided visual task completion.

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Keras Image Embeddings using Contrastive Loss

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Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.

3D Infomax improves GNNs for Molecular Property Prediction Video | Paper We pre-train GNNs to understand the geometry of molecules given only their 2D

Hannes Stärk 95 Dec 30, 2022