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Vision Meets Drones:

A Challenge

无人机视觉挑战赛

After ECCV-VisDrone 2018, ICCV-VisDrone 2019, ECCV-VisDrone 2020, ICCV-VisDrone 2021, and PRCV- VisDrone 2022,  VisDrone Challenge will be held on the ICCV 2023 workshop“Vision Meets Drones: A Challenge”(or VisDrone 2023) in Paris, France, for various core vision tasks on drone platform. We invite researchers to participate in the challenge and to evaluate and discuss their research at the workshop, as well as to submit papers describing research, experiments, or applications on drones.  

 ICCV-VisDrone 2023竞赛和研讨会将于2023年10月3日在法国巴黎举办。VisDrone2023挑战赛分为两个赛道,包括Object Detection Challenge(目标检测)以及Zero-Shot Detection Challenge(零样本目标检测)。本届比赛由天津大学、西北工业大学、浙江大学、香港科技大学、香港中文大学、中山大学以及澳大利亚国立大学共同承办,并获得了知名无人机公司一飞智控的赞助和支持。本届比赛鼓励各个参赛队伍使用大模型以及额外数据参赛,以探索空对地小目标检测性能的上限以及大模型的泛化能力。

CHALLENGE TASKS

挑战任务

1

Object Detection Challenge

目标检测

The task aims to detect objects of predefined categories (e.g., cars and pedestrians) from videos taken from drones.

该任务旨在从无人机拍摄的视频中检测预定义类别对象。

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2

Zero-Shot Detection Challenge

零样本检测

The task aims to detect objects of unavailable categories during training from remote sensing images taken from drones or satellites.

该任务旨在从无人机或卫星拍摄的遥感图像中检测训练期间不可用的类别对象。

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DETAILS 

大赛细节

01

DATE 日期

[06.01]: Training, validation and testing data released

开放训练、验证和测试数据集

[06.15]: Evaluation software released

开放结果评估提交通道

[07.15]: Result submission deadline

各赛道截止提交

[10.03]: Challenge results released

公布比赛结果

[10.03]: Winner presents at ICCV 2023 Workshop 

冠军在ICCV 2023研讨会上发表演讲

The deadline for the competition is 24:00 on July 15th 2023, GMT time

比赛截止时间2023年7月15日24:00 格林威治标准时间

02

AWARD  奖项

The top three from each track will receive a certificate.

The track winner will be awarded 10000RMB.

每个赛道的前三名将获得比赛证书,赛道冠军奖励10000RMB。

Champion will be invited to make a presentation.

The use of foundation model and additional dataset is also encouraged.

冠军将会受邀作报告,鼓励使用大模型和额外数据。

03

PARTICIPATION 参赛通道 

website:http://aiskyeye.com/home/

Advisory Committee

咨询委员会

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Qinghua Hu

胡清华

Professor

教授

Tianjin University

天津大学

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Junwei Han

韩军伟

Professor

教授

Northwestern Polytechnical University

西北工业大学

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Fatih Porikli

法提·波里克利

Professor

教授

Australian National University

澳大利亚国立大学

Organizing Committee

组委会

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Pengfei Zhu

朱鹏飞

Associate Professor

副教授

Tianjin University

天津大学

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Dingwen Zhang

张鼎文

Professor

教授

Northwestern Polytechnical University

西北工业大学

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Wenguan Wang

王文冠

Professor

研究员

Zhejiang University

浙江大学

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Zhijian He

何志坚

Research Associate

博士后

The Hong Kong University of Science and Technology

香港科技大学

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Lei Xue

薛磊

Associate Professor

副教授

Sun Yat-Sen University

中山大学

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Yixuan Yuan

袁奕萱

Assistant Professor

助理教授

Chinese University of Hong Kong

香港中文大学

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Yu Wang

王煜

Associate Professor

副研究员

Tianjin University

天津大学

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Bing Cao

曹兵

Associate Professor

副研究员

Tianjin University

天津大学

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Xinjie Yao

姚鑫杰

Ph.D. Student

博士生

Tianjin University

天津大学

Laboratory

实验室介绍

The lab of Machine Learning and Data Mining at Tianjin University focuses on research in fundamental and applied aspects of machine learning, data mining, and pattern recognition, with a focus on the labeling, understanding, clustering, classification, and regression analysis of large-scale multi-source heterogeneous uncertain data. The lab has achieved significant research achievements in applications such as massive audio and video understanding, intelligent driving, intelligent unmanned systems, disaster space weather forecasting, and large equipment health monitoring. The lab has been selected as a Tianjin 131 Innovative Team and has been granted the Tianjin Key Laboratory of Machine Learning and the Engineering Research Center for Urban Intelligence and Digital Governance by the Ministry of Education. In recent years, the team has been funded by the National 973 Project, the National Key R&D Program, and the National Natural Science Foundation of China. They have published a series of papers in renowned international journals such as IEEE TPAMI, IJCV, IEEE TIP, IEEE TKDE, and international top conferences such as ICML, NeurIPS, ICLR, ICCV, and CVPR. They have also won several awards such as the Best Paper Award at the CCDM, CCF-AI, CCML, ICMLC, and ICME conferences. Members of the team have received support from various talent programs such as the National Natural Science Foundation of China's Distinguished Young Scholars Program, Outstanding Youth Science Fund, Youth Top-notch Talents Support Program, New Century Excellent Talents Support Program, Postdoctoral Innovation Talents Support Program, and the China Association for Science and Technology's Young Talent Support Program.

  The laboratory is always welcoming scholars and students who are interested in conducting research on the fundamentals and applications of machine learning and pattern recognition. If you are interested, please send your resume to zhupengfei@tju.edu.cn.

SPONSOR

赞助商

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Contact  us

联系我们

website:http://aiskyeye.com/home/

mail:tju.drone.vision@gmail.com

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pytorch/vision: 一个基于 PyTorch 的计算机视觉库,提供了各种计算机视觉算法和工具,适合用于实现计算机视觉应用程序。
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