the official code for ICRA 2021 Paper: "Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation"

Related tags

Deep LearningG2S
Overview

G2S

This is the official code for ICRA 2021 Paper: Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation by Hemang Chawla, Arnav Varma, Elahe Arani and Bahram Zonooz.

alt text

G2S (GPS-to-Scale) Loss is a dynamically-weighted loss that can be added to the appearance-based losses to train any monocular self-supervised depth estimation architecture to get scale-consistant and scale-aware depth estimates at inference.

Here, we provide helper GPS dataloader and the G2S loss classes for using this loss with any model.

For details, please see the Paper and Presentation.

KITTI GPS

The GPS files containing geodesic gps information of raw kitti dataset in local coordinates for training with the g2s loss can be found in the assets folder as kitti_gps_raw.zip.
Unzip the file at /path/to/KITTI/raw_data/sync to merge the GPS files in the expected directory tree structure.

Usage

You can use the G2S class in lossG2S.py within your project for scale-consistent and -aware predictions. This requires using the copresent GPS modality along with images. To load the GPS, please adopt the GPSDataloader class within dataloaderGPS.py into your images dataloader.

Cite Our Work

If you find the code useful in your research, please consider citing our paper:

@inproceedings{chawlavarma2021multimodal,
	author={H. {Chawla} and A. {Varma} and E. {Arani} and B. {Zonooz}},
	booktitle={2021 IEEE International Conference on Robotics and Automation (ICRA)},
	title={Multimodal Scale Consistency and Awareness for Monocular Self-Supervised
	Depth Estimation},
	location={Xi’an, China},
	publisher={IEEE (in press)},
	year={2021}
}

License

This project is licensed under the terms of the MIT license.

Owner
NeurAI
Located at the brain port of Netherlands, the Advanced Research Lab is an innovation center within the NavInfo group. We have a diverse energetic team of resear
NeurAI
Source Code for our paper: Understand me, if you refer to Aspect Knowledge: Knowledge-aware Gated Recurrent Memory Network

KaGRMN-DSG_ABSA This repository contains the PyTorch source Code for our paper: Understand me, if you refer to Aspect Knowledge: Knowledge-aware Gated

XingBowen 4 May 20, 2022
Calibrate your listeners! Robust communication-based training for pragmatic speakers. Findings of EMNLP 2021.

Calibrate your listeners! Robust communication-based training for pragmatic speakers Rose E. Wang, Julia White, Jesse Mu, Noah D. Goodman Findings of

Rose E. Wang 3 Apr 02, 2022
[CIKM 2019] Code and dataset for "Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction"

FiGNN for CTR prediction The code and data for our paper in CIKM2019: Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Predicti

Big Data and Multi-modal Computing Group, CRIPAC 75 Dec 30, 2022
Stock-Prediction - prediction of stock market movements using sentiment analysis and deep learning.

Stock-Prediction- In this project, we aim to enhance the prediction of stock market movements using sentiment analysis and deep learning. We divide th

5 Jan 25, 2022
Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping

Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping

Yam Peleg 63 Sep 21, 2022
A Kitti Road Segmentation model implemented in tensorflow.

KittiSeg KittiSeg performs segmentation of roads by utilizing an FCN based model. The model achieved first place on the Kitti Road Detection Benchmark

Marvin Teichmann 890 Jan 04, 2023
Face Mask Detection is a project to determine whether someone is wearing mask or not, using deep neural network.

face-mask-detection Face Mask Detection is a project to determine whether someone is wearing mask or not, using deep neural network. It contains 3 scr

amirsalar 13 Jan 18, 2022
Technical experimentations to beat the stock market using deep learning :chart_with_upwards_trend:

DeepStock Technical experimentations to beat the stock market using deep learning. Experimentations Deep Learning Stock Prediction with Daily News Hea

Keon 449 Dec 29, 2022
Moiré Attack (MA): A New Potential Risk of Screen Photos [NeurIPS 2021]

Moiré Attack (MA): A New Potential Risk of Screen Photos [NeurIPS 2021] This repository is the official implementation of Moiré Attack (MA): A New Pot

Dantong Niu 22 Dec 24, 2022
Additional functionality for use with fastai’s medical imaging module

fmi Adding additional functionality to fastai's medical imaging module To learn more about medical imaging using Fastai you can view my blog Install g

14 Oct 31, 2022
Seq2seq - Sequence to Sequence Learning with Keras

Seq2seq Sequence to Sequence Learning with Keras Hi! You have just found Seq2Seq. Seq2Seq is a sequence to sequence learning add-on for the python dee

Fariz Rahman 3.1k Dec 18, 2022
Dense Prediction Transformers

Vision Transformers for Dense Prediction This repository contains code and models for our paper: Vision Transformers for Dense Prediction René Ranftl,

Intelligent Systems Lab Org 1.3k Jan 02, 2023
This project aim to create multi-label classification annotation tool to boost annotation speed and make it more easier.

This project aim to create multi-label classification annotation tool to boost annotation speed and make it more easier.

4 Aug 02, 2022
Unofficial PyTorch implementation of MobileViT based on paper "MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer".

MobileViT RegNet Unofficial PyTorch implementation of MobileViT based on paper MOBILEVIT: LIGHT-WEIGHT, GENERAL-PURPOSE, AND MOBILE-FRIENDLY VISION TR

Hong-Jia Chen 91 Dec 02, 2022
This is the official implementation of "One Question Answering Model for Many Languages with Cross-lingual Dense Passage Retrieval".

CORA This is the official implementation of the following paper: Akari Asai, Xinyan Yu, Jungo Kasai and Hannaneh Hajishirzi. One Question Answering Mo

Akari Asai 59 Dec 28, 2022
CVPR2022 (Oral) - Rethinking Semantic Segmentation: A Prototype View

Rethinking Semantic Segmentation: A Prototype View Rethinking Semantic Segmentation: A Prototype View, Tianfei Zhou, Wenguan Wang, Ender Konukoglu and

Tianfei Zhou 239 Dec 26, 2022
KinectFusion implemented in Python with PyTorch

KinectFusion implemented in Python with PyTorch This is a lightweight Python implementation of KinectFusion. All the core functions (TSDF volume, fram

Jingwen Wang 80 Jan 03, 2023
In-Place Activated BatchNorm for Memory-Optimized Training of DNNs

In-Place Activated BatchNorm In-Place Activated BatchNorm for Memory-Optimized Training of DNNs In-Place Activated BatchNorm (InPlace-ABN) is a novel

1.3k Dec 29, 2022
Make differentially private training of transformers easy for everyone

private-transformers This codebase facilitates fast experimentation of differentially private training of Hugging Face transformers. What is this? Why

Xuechen Li 73 Dec 28, 2022
Visualizing Yolov5's layers using GradCam

YOLO-V5 GRADCAM I constantly desired to know to which part of an object the object-detection models pay more attention. So I searched for it, but I di

Pooya Mohammadi Kazaj 200 Jan 01, 2023