Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark

Related tags

Deep LearningVISO
Overview

Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark

This is the official website of the VISO (VIdeo Satellite Objects) dataset. [Download]

(1) Data

This dataset is a large-scale dataset for moving object detection and tracking in satellite videos, which consists of 40 satellite videos captured by Jilin-1 satellite platforms. Each image has a resolution of 12000x5000 and contains a great number of objects with different scales. Four common types of vechicles, including plane, car, ship, and train, are manually-labeled. A total of 853,911 instances are labeled by axis-aligned bounding boxes.

(2) Benchmark

We also build a new satellite video benchmark to fairly and extensively evaluate the performance of existing methods in several sub-tasks, including moving object detection, single-object tracking, and multi-object tracking.

  • Moving Object Detection:

  • Single Object Tracking:

  • Multiple Object Tracking:

(3) Demo

Owner
Qingyong
Ph.D. student :man_student: in the Department of Computer Science at the University of Oxford :cn:
Qingyong
Code for "Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereo"

Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereo This repository includes the source code for our CVPR 2021 paper on multi-view mult

Jiahao Lin 66 Jan 04, 2023
A python module for scientific analysis of 3D objects based on VTK and Numpy

A lightweight and powerful python module for scientific analysis and visualization of 3d objects.

Marco Musy 1.5k Jan 06, 2023
A universal memory dumper using Frida

Fridump Fridump (v0.1) is an open source memory dumping tool, primarily aimed to penetration testers and developers. Fridump is using the Frida framew

551 Jan 07, 2023
UltraGCN: An Ultra Simplification of Graph Convolutional Networks for Recommendation

UltraGCN This is our Pytorch implementation for our CIKM 2021 paper: Kelong Mao, Jieming Zhu, Xi Xiao, Biao Lu, Zhaowei Wang, Xiuqiang He. UltraGCN: A

XUEPAI 93 Jan 03, 2023
A framework for Quantification written in Python

QuaPy QuaPy is an open source framework for quantification (a.k.a. supervised prevalence estimation, or learning to quantify) written in Python. QuaPy

41 Dec 14, 2022
TensorFlow ROCm port

Documentation TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, a

ROCm Software Platform 622 Jan 09, 2023
Evolving neural network parameters in JAX.

Evolving Neural Networks in JAX This repository holds code displaying techniques for applying evolutionary network training strategies in JAX. Each sc

Trevor Thackston 6 Feb 12, 2022
SymPy-powered, Wolfram|Alpha-like answer engine totally in your browser, without backend computation

SymPy Beta SymPy Beta is a fork of SymPy Gamma. The purpose of this project is to run a SymPy-powered, Wolfram|Alpha-like answer engine totally in you

Liumeo 25 Dec 21, 2022
Sentiment analysis translations of the Bhagavad Gita

Sentiment and Semantic Analysis of Bhagavad Gita Translations It is well known that translations of songs and poems not only breaks rhythm and rhyming

Machine learning and Bayesian inference @ UNSW Sydney 3 Aug 01, 2022
Aesara is a Python library that allows one to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.

Aesara is a Python library that allows one to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.

Aesara 898 Jan 07, 2023
An Ensemble of CNN (Python 3.5.1 Tensorflow 1.3 numpy 1.13)

An Ensemble of CNN (Python 3.5.1 Tensorflow 1.3 numpy 1.13)

0 May 06, 2022
Multi-query Video Retreival

Multi-query Video Retreival

Princeton Visual AI Lab 17 Nov 22, 2022
QAT(quantize aware training) for classification with MQBench

MQBench Quantization Aware Training with PyTorch I am using MQBench(Model Quantization Benchmark)(http://mqbench.tech/) to quantize the model for depl

Ling Zhang 29 Nov 18, 2022
Code for paper entitled "Improving Novelty Detection using the Reconstructions of Nearest Neighbours"

NLN: Nearest-Latent-Neighbours A repository containing the implementation of the paper entitled Improving Novelty Detection using the Reconstructions

Michael (Misha) Mesarcik 4 Dec 14, 2022
[ICLR2021oral] Rethinking Architecture Selection in Differentiable NAS

DARTS-PT Code accompanying the paper ICLR'2021: Rethinking Architecture Selection in Differentiable NAS Ruochen Wang, Minhao Cheng, Xiangning Chen, Xi

Ruochen Wang 86 Dec 27, 2022
A Python module for parallel optimization of expensive black-box functions

blackbox: A Python module for parallel optimization of expensive black-box functions What is this? A minimalistic and easy-to-use Python module that e

Paul Knysh 426 Dec 08, 2022
LRBoost is a scikit-learn compatible approach to performing linear residual based stacking/boosting.

LRBoost is a sckit-learn compatible package for linear residual boosting. LRBoost combines a linear estimator and a non-linear estimator to leverage t

Andrew Patton 5 Nov 23, 2022
Official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition" in AAAI2022.

AimCLR This is an official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Reco

Gty 44 Dec 17, 2022
A smaller subset of 10 easily classified classes from Imagenet, and a little more French

Imagenette 🎶 Imagenette, gentille imagenette, Imagenette, je te plumerai. 🎶 (Imagenette theme song thanks to Samuel Finlayson) NB: Versions of Image

fast.ai 718 Jan 01, 2023
This repository is for Contrastive Embedding Distribution Refinement and Entropy-Aware Attention Network (CEDR)

CEDR This repository is for Contrastive Embedding Distribution Refinement and Entropy-Aware Attention Network (CEDR) introduced in the following paper

phoenix 3 Feb 27, 2022