Tiny Object Detection in Aerial Images.

Related tags

Deep LearningAI-TOD
Overview

AI-TOD

AI-TOD is a dataset for tiny object detection in aerial images.

[Paper] [Dataset]

Description

AI-TOD comes with 700,621 object instances for eight categories across 28,036 aerial images. Compared to existing object detection datasets in aerial images, the mean size of objects in AI-TOD is about 12.8 pixels, which is much smaller than others.

Download

You can download the dataset on Google Driver.

Evaluation

Training and Validation sets are publicly available. If you want to report the accuracies on test set, please send the results on test set to [email protected].

Citation

If you use this dataset in your research, please cite this paper.

@inproceedings{AI-TOD_2020_ICPR,
    title={Tiny Object Detection in Aerial Images},
    author={Wang, Jinwang and Yang, Wen and Guo, Haowen and Zhang, Ruixiang and Xia, Gui-Song},
    booktitle=ICPR,
    pages={3791--3798},
    year={2021},
}
Owner
jwwangchn
Python;MATLAB;C++;Machine Learning;Deep Learning;Computer Vision;Pytorch
jwwangchn
Can we do Customers Segmentation using PHP and Unsupervized Machine Learning ? Yes we can ! 🤡

Customers Segmentation using PHP and Rubix ML PHP Library Can we do Customers Segmentation using PHP and Unsupervized Machine Learning ? Yes we can !

Mickaël Andrieu 11 Oct 08, 2022
source code of “Visual Saliency Transformer” (ICCV2021)

Visual Saliency Transformer (VST) source code for our ICCV 2021 paper “Visual Saliency Transformer” by Nian Liu, Ni Zhang, Kaiyuan Wan, Junwei Han, an

89 Dec 21, 2022
MinkLoc3D-SI: 3D LiDAR place recognition with sparse convolutions,spherical coordinates, and intensity

MinkLoc3D-SI: 3D LiDAR place recognition with sparse convolutions,spherical coordinates, and intensity Introduction The 3D LiDAR place recognition aim

16 Dec 08, 2022
This is a re-implementation of TransGAN: Two Pure Transformers Can Make One Strong GAN (CVPR 2021) in PyTorch.

TransGAN: Two Transformers Can Make One Strong GAN [YouTube Video] Paper Authors: Yifan Jiang, Shiyu Chang, Zhangyang Wang CVPR 2021 This is re-implem

Ahmet Sarigun 79 Jan 05, 2023
Official implementation of the paper Image Generators with Conditionally-Independent Pixel Synthesis https://arxiv.org/abs/2011.13775

CIPS -- Official Pytorch Implementation of the paper Image Generators with Conditionally-Independent Pixel Synthesis Requirements pip install -r requi

Multimodal Lab @ Samsung AI Center Moscow 201 Dec 21, 2022
Text completion with Hugging Face and TensorFlow.js running on Node.js

Katana ML Text Completion 🤗 Description Runs with with Hugging Face DistilBERT and TensorFlow.js on Node.js distilbert-model - converter from Hugging

Katana ML 2 Nov 04, 2022
SegNet-like Autoencoders in TensorFlow

SegNet SegNet is a TensorFlow implementation of the segmentation network proposed by Kendall et al., with cool features like strided deconvolution, a

Andrea Azzini 66 Nov 05, 2021
Seeing if I can put together an interactive version of 3b1b's Manim in Streamlit

streamlit-manim Seeing if I can put together an interactive version of 3b1b's Manim in Streamlit Installation I had to install pango with sudo apt-get

Adrien Treuille 6 Aug 03, 2022
Do you like Quick, Draw? Well what if you could train/predict doodles drawn inside Streamlit? Also draws lines, circles and boxes over background images for annotation.

Streamlit - Drawable Canvas Streamlit component which provides a sketching canvas using Fabric.js. Features Draw freely, lines, circles, boxes and pol

Fanilo Andrianasolo 325 Dec 28, 2022
Safe Bayesian Optimization

SafeOpt - Safe Bayesian Optimization This code implements an adapted version of the safe, Bayesian optimization algorithm, SafeOpt [1], [2]. It also p

Felix Berkenkamp 111 Dec 11, 2022
Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)

Junction Tree Variational Autoencoder for Molecular Graph Generation Official implementation of our Junction Tree Variational Autoencoder https://arxi

Wengong Jin 418 Jan 07, 2023
Official implementation of "UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer"

[AAAI2022] UCTransNet This repo is the official implementation of "UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspectiv

Haonan Wang 199 Jan 03, 2023
A Number Recognition algorithm

Paddle-VisualAttention Results_Compared SVHN Dataset Methods Steps GPU Batch Size Learning Rate Patience Decay Step Decay Rate Training Speed (FPS) Ac

1 Nov 12, 2021
Project page for our ICCV 2021 paper "The Way to my Heart is through Contrastive Learning"

The Way to my Heart is through Contrastive Learning: Remote Photoplethysmography from Unlabelled Video This is the official project page of our ICCV 2

36 Jan 06, 2023
IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales

IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales. In this case, we ended up using XGBoost because it was the o

1 Jan 04, 2022
Convert BART models to ONNX with quantization. 3X reduction in size, and upto 3X boost in inference speed

fast-Bart Reduction of BART model size by 3X, and boost in inference speed up to 3X BART implementation of the fastT5 library (https://github.com/Ki6a

Siddharth Sharma 19 Dec 09, 2022
🐦 Quickly annotate data from the comfort of your Jupyter notebook

🐦 pigeon - Quickly annotate data on Jupyter Pigeon is a simple widget that lets you quickly annotate a dataset of unlabeled examples from the comfort

Anastasis Germanidis 647 Jan 05, 2023
Towards Representation Learning for Atmospheric Dynamics (AtmoDist)

Towards Representation Learning for Atmospheric Dynamics (AtmoDist) The prediction of future climate scenarios under anthropogenic forcing is critical

Sebastian Hoffmann 4 Dec 15, 2022
ManiSkill-Learn is a framework for training agents on SAPIEN Open-Source Manipulation Skill Challenge (ManiSkill Challenge), a large-scale learning-from-demonstrations benchmark for object manipulation.

ManiSkill-Learn ManiSkill-Learn is a framework for training agents on SAPIEN Open-Source Manipulation Skill Challenge, a large-scale learning-from-dem

Hao Su's Lab, UCSD 48 Dec 30, 2022
Repo for the Video Person Clustering dataset, and code for the associated paper

Video Person Clustering Repo for the Video Person Clustering dataset, and code for the associated paper. This reporsitory contains the Video Person Cl

Andrew Brown 47 Nov 02, 2022