Pathdreamer: A World Model for Indoor Navigation

Overview

Pathdreamer: A World Model for Indoor Navigation

This repository hosts the open source code for Pathdreamer, to be presented at ICCV 2021.

Video Results

Paper | Project Webpage | Colab Demo

Setup instructions

Environment

Set up virtualenv, and install required libraries:

virtualenv venv
source venv/bin/activate
pip install -r requirements.txt

Add the Pathdreamer library to PYTHONPATH:

export PYTHONPATH=$PYTHONPATH:/home/path/to/pathdreamer_root/

Downloading Pretrained Checkpoints

We provide a pretrained checkpoint which can be acquired by running:

wget https://storage.googleapis.com/gresearch/pathdreamer/ckpt.tar -P data/
tar -xf data/ckpt.tar --directory data/

The results will be extracted to the data/ckpt directory. Two checkpoints are provided, one for the Stage 1 model (Structure Generator), and another for the Stage 2 model (Image Generator).

Colab Demo

Pathdreamer_Example_Colab.ipynb [click to launch in Google Colab] shows how to setup and run the pretrained Pathdreamer model for inference. It includes examples on synthesizing image sequences and continuous video sequences for arbitrary navigation trajectories.

Citation

If you find this work useful, please consider citing:

@inproceedings{koh2021pathdreamer,
  title={Pathdreamer: A World Model for Indoor Navigation},
  author={Koh, Jing Yu and Lee, Honglak and Yang, Yinfei and Baldridge, Jason and Anderson, Peter},
  journal={Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
  year={2021}
}

License

Pathdreamer is released under the Apache 2.0 license. The Matterport3D dataset is governed by the Matterport3D Terms of Use.

Disclaimer

Not an official Google product.

Owner
Google Research
Google Research
Wandb-predictions - WANDB Predictions With Python

WANDB API CI/CD Below we capture the CI/CD scenarios that we would expect with o

Anish Shah 6 Oct 07, 2022
Cobalt Strike teamserver detection.

Cobalt-Strike-det Cobalt Strike teamserver detection. usage: cobaltstrike_verify.py [-l TARGETS] [-t THREADS] optional arguments: -h, --help show this

TimWhite 17 Sep 27, 2022
🌳 A Python-inspired implementation of the Optimum-Path Forest classifier.

OPFython: A Python-Inspired Optimum-Path Forest Classifier Welcome to OPFython. Note that this implementation relies purely on the standard LibOPF. Th

Gustavo Rosa 30 Jan 04, 2023
Rapid experimentation and scaling of deep learning models on molecular and crystal graphs.

LitMatter A template for rapid experimentation and scaling deep learning models on molecular and crystal graphs. How to use Clone this repository and

Nathan Frey 32 Dec 06, 2022
Pansharpening by convolutional neural networks in the full resolution framework

Z-PNN: Zoom Pansharpening Neural Network Pansharpening by convolutional neural networks in the full resolution framework is a deep learning method for

20 Nov 24, 2022
Generative vs Discriminative: Rethinking The Meta-Continual Learning (NeurIPS 2021)

Generative vs Discriminative: Rethinking The Meta-Continual Learning (NeurIPS 2021) In this repository we provide PyTorch implementations for GeMCL; a

4 Apr 15, 2022
Intel® Neural Compressor is an open-source Python library running on Intel CPUs and GPUs

Intel® Neural Compressor targeting to provide unified APIs for network compression technologies, such as low precision quantization, sparsity, pruning, knowledge distillation, across different deep l

Intel Corporation 846 Jan 04, 2023
Adversarial Attacks are Reversible via Natural Supervision

Adversarial Attacks are Reversible via Natural Supervision ICCV2021 Citation @InProceedings{Mao_2021_ICCV, author = {Mao, Chengzhi and Chiquier

Computer Vision Lab at Columbia University 20 May 22, 2022
Kindle is an easy model build package for PyTorch.

Kindle is an easy model build package for PyTorch. Building a deep learning model became so simple that almost all model can be made by copy and paste from other existing model codes. So why code? wh

Jongkuk Lim 77 Nov 11, 2022
Learning hierarchical attention for weakly-supervised chest X-ray abnormality localization and diagnosis

Hierarchical Attention Mining (HAM) for weakly-supervised abnormality localization This is the official PyTorch implementation for the HAM method. Pap

Xi Ouyang 22 Jan 02, 2023
MoCoPnet - Deformable 3D Convolution for Video Super-Resolution

Deformable 3D Convolution for Video Super-Resolution Pytorch implementation of l

Xinyi Ying 28 Dec 15, 2022
This repository focus on Image Captioning & Video Captioning & Seq-to-Seq Learning & NLP

Awesome-Visual-Captioning Table of Contents ACL-2021 CVPR-2021 AAAI-2021 ACMMM-2020 NeurIPS-2020 ECCV-2020 CVPR-2020 ACL-2020 AAAI-2020 ACL-2019 NeurI

Ziqi Zhang 362 Jan 03, 2023
Implement the Pareto Optimizer and pcgrad to make a self-adaptive loss for multi-task

multi-task_losses_optimizer Implement the Pareto Optimizer and pcgrad to make a self-adaptive loss for multi-task 已经实验过了,不会有cuda out of memory情况 ##Par

14 Dec 25, 2022
PyTorch Implementation for Fracture Detection in Wrist Bone X-ray Images

wrist-d PyTorch Implementation for Fracture Detection in Wrist Bone X-ray Images note: Paper: Under Review at MPDI Diagnostics Submission Date: Novemb

Fatih UYSAL 5 Oct 12, 2022
Code for "Solving Graph-based Public Good Games with Tree Search and Imitation Learning"

Code for "Solving Graph-based Public Good Games with Tree Search and Imitation Learning" This is the code for the paper Solving Graph-based Public Goo

Victor-Alexandru Darvariu 3 Dec 05, 2022
Using this codebase as a tool for my own research. Making some modifications to the original repo for my own purposes.

For SwapNet Create a list.txt file containing all the images to process. This can be done with the GNU find command: find path/to/input/folder -name '

Andrew Jong 2 Nov 10, 2021
Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.

Non-Metric Space Library (NMSLIB) Important Notes NMSLIB is generic but fast, see the results of ANN benchmarks. A standalone implementation of our fa

2.9k Jan 04, 2023
Count the MACs / FLOPs of your PyTorch model.

THOP: PyTorch-OpCounter How to install pip install thop (now continously intergrated on Github actions) OR pip install --upgrade git+https://github.co

Ligeng Zhu 3.9k Dec 29, 2022
3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks

3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks Introduction This repository contains the code and models for the follo

124 Jan 06, 2023