Official repository of ICCV21 paper "Viewpoint Invariant Dense Matching for Visual Geolocalization"

Related tags

Deep Learninggeo_warp
Overview

Viewpoint Invariant Dense Matching for Visual Geolocalization: PyTorch implementation

This is the implementation of the ICCV21 paper:

G Berton, C. Masone, V. Paolicelli and B. Caputo, Viewpoint Invariant Dense Matching for Visual Geolocalization

Setup

First download the baseline models which have been trained following the training procedure in the NetVLAD paper. We provide a script to download the six models used, which are a combination of 3 backbone encoders (AlexNet, VGG-16 and ResNet-50) with 2 pooling/aggregation layers (GeM and NetVLAD).

python download_pretrained_baselines.py

Then you should prepare your geo-localization dataset, so that the directory tree is as such:

dataset_name
└── images
    ├── train
    │   ├── gallery
    │   └── queries
    ├── val
    │   ├── gallery
    │   └── queries
    └── test
        ├── gallery
        └── queries

and the images are named as @UTM [email protected] [email protected]@.jpg

Dependencies

See requirements.txt

Training

You can train the model using the train.py, here's an example with the lightest/fastest model (i.e. AlexNet + GeM):

python train.py --arch alexnet --pooling gem --resume_fe pretrained_baselines/alexnet_gem.pth

For a full set of options, run python train.py -h. The script will create a folder under ./runs/default/YYYY-MM-DD_HH-mm-ss where logs and checkpoints will be saved.

Evaluation

Coming soon.

BibTeX

If you use this code in your project, please cite us using:

@InProceedings{Berton_ICCV_2021,
    author    = {Berton, Gabriele and Masone, Carlo and Paolicelli, Valerio and Caputo, Barbara},
    title     = {Viewpoint Invariant Dense Matching for Visual Geolocalization},
    booktitle = ICCV,
    month     = {October},
    year      = {2021},
    pages     = {12169-12178}
}
Owner
Gabriele Berton
Gabriele Berton
Research on controller area network Intrusion Detection Systems

Group members information Member 1: Lixue Liang Member 2: Yuet Lee Chan Member 3: Xinruo Zhang Member 4: Yifei Han User Manual Generate Attack Packets

Roche 4 Aug 30, 2022
ICNet for Real-Time Semantic Segmentation on High-Resolution Images, ECCV2018

ICNet for Real-Time Semantic Segmentation on High-Resolution Images by Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia, details a

Hengshuang Zhao 594 Dec 31, 2022
A Quick and Dirty Progressive Neural Network written in TensorFlow.

prog_nn .▄▄ · ▄· ▄▌ ▐ ▄ ▄▄▄· ▐ ▄ ▐█ ▀. ▐█▪██▌•█▌▐█▐█ ▄█▪ •█▌▐█ ▄▀▀▀█▄▐█▌▐█▪▐█▐▐▌ ██▀

SynPon 53 Dec 12, 2022
Learning cell communication from spatial graphs of cells

ncem Features Repository for the manuscript Fischer, D. S., Schaar, A. C. and Theis, F. Learning cell communication from spatial graphs of cells. 2021

Theis Lab 77 Dec 30, 2022
An Unsupervised Graph-based Toolbox for Fraud Detection

An Unsupervised Graph-based Toolbox for Fraud Detection Introduction: UGFraud is an unsupervised graph-based fraud detection toolbox that integrates s

SafeGraph 99 Dec 11, 2022
Tech Resources for Academic Communities

Free tech resources for faculty, students, researchers, life-long learners, and academic community builders for use in tech based courses, workshops, and hackathons.

Microsoft 2.5k Jan 04, 2023
An open source bike computer based on Raspberry Pi Zero (W, WH) with GPS and ANT+. Including offline map and navigation.

Pi Zero Bikecomputer An open-source bike computer based on Raspberry Pi Zero (W, WH) with GPS and ANT+ https://github.com/hishizuka/pizero_bikecompute

hishizuka 264 Jan 02, 2023
A modular PyTorch library for optical flow estimation using neural networks

A modular PyTorch library for optical flow estimation using neural networks

neu-vig 113 Dec 20, 2022
Library to enable Bayesian active learning in your research or labeling work.

Bayesian Active Learning (BaaL) BaaL is an active learning library developed at ElementAI. This repository contains techniques and reusable components

ElementAI 687 Dec 25, 2022
YoloAll is a collection of yolo all versions. you you use YoloAll to test yolov3/yolov5/yolox/yolo_fastest

官方讨论群 QQ群:552703875 微信群:15158106211(先加作者微信,再邀请入群) YoloAll项目简介 YoloAll是一个将当前主流Yolo版本集成到同一个UI界面下的推理预测工具。可以迅速切换不同的yolo版本,并且可以针对图片,视频,摄像头码流进行实时推理,可以很方便,直观

DL-Practise 244 Jan 01, 2023
Denoising Diffusion Probabilistic Models

Denoising Diffusion Probabilistic Models Jonathan Ho, Ajay Jain, Pieter Abbeel Paper: https://arxiv.org/abs/2006.11239 Website: https://hojonathanho.g

Jonathan Ho 1.5k Jan 08, 2023
A real-time motion capture system that estimates poses and global translations using only 6 inertial measurement units

TransPose Code for our SIGGRAPH 2021 paper "TransPose: Real-time 3D Human Translation and Pose Estimation with Six Inertial Sensors". This repository

Xinyu Yi 261 Dec 31, 2022
GPU Accelerated Non-rigid ICP for surface registration

GPU Accelerated Non-rigid ICP for surface registration Introduction Preivous Non-rigid ICP algorithm is usually implemented on CPU, and needs to solve

Haozhe Wu 144 Jan 04, 2023
ETMO: Evolutionary Transfer Multiobjective Optimization

ETMO: Evolutionary Transfer Multiobjective Optimization To promote the research on ETMO, benchmark problems are of great importance to ETMO algorithm

Songbai Liu 0 Mar 16, 2021
General purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends)

General purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usec

The Kompute Project 1k Jan 06, 2023
[CVPR 2021] Few-shot 3D Point Cloud Semantic Segmentation

Few-shot 3D Point Cloud Semantic Segmentation Created by Na Zhao from National University of Singapore Introduction This repository contains the PyTor

117 Dec 27, 2022
(CVPR2021) ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic

ClassSR (CVPR2021) ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic Paper Authors: Xiangtao Kong, Hengyuan

Xiangtao Kong 308 Jan 05, 2023
DROPO: Sim-to-Real Transfer with Offline Domain Randomization

DROPO: Sim-to-Real Transfer with Offline Domain Randomization Gabriele Tiboni, Karol Arndt, Ville Kyrki. This repository contains the code for the pap

Gabriele Tiboni 8 Dec 19, 2022
Pytorch code for paper "Image Compressed Sensing Using Non-local Neural Network" TMM 2021.

NL-CSNet-Pytorch Pytorch code for paper "Image Compressed Sensing Using Non-local Neural Network" TMM 2021. Note: this repo only shows the strategy of

WenxueCui 7 Nov 07, 2022
Implementation for paper "Towards the Generalization of Contrastive Self-Supervised Learning"

Contrastive Self-Supervised Learning on CIFAR-10 Paper "Towards the Generalization of Contrastive Self-Supervised Learning", Weiran Huang, Mingyang Yi

Weiran Huang 13 Nov 30, 2022