RESEARCH

COMPUTER VISION

DeepGlobe 2018: A Challenge to Parse the Earth through Satellite Images

June 18, 2018

Abstract

We present the DeepGlobe 2018 Satellite Image Understanding Challenge, which includes three public competitions for segmentation, detection, and classification tasks on satellite images. Similar to other challenges in computer vision domain such as DAVIS and COCO, DeepGlobe proposes three datasets and corresponding evaluation methodologies, coherently bundled in three competitions with a dedicated workshop co-located with CVPR 2018. We observed that satellite imagery is a rich and structured source of information, yet it is less investigated than everyday images by computer vision researchers. However, bridging modern computer vision with remote sensing data analysis could have critical impact to the way we understand our environment and lead to major breakthroughs in global urban planning or climate change research. Keeping such bridging objective in mind, DeepGlobe aims to bring together researchers from different domains to raise awareness of remote sensing in the computer vision community and vice-versa. We aim to improve and evaluate state-of-the-art satellite image understanding approaches, which can hopefully serve as reference benchmarks for future research in the same topic. In this paper, we analyze characteristics of each dataset, define the evaluation criteria of the competitions, and provide baselines for each task.

Download the Paper

AUTHORS

Written by

Ilke Demir

Forest Hughes

Guan Pang

Jing Huang

Saikat Basu

David Lindenbaum

Devis Tuia

Krzysztof Koperski

Ramesh Raskar

Publisher

CVPR

Research Topics

Computer Vision

Related Publications

July 02, 2024

GRAPHICS

COMPUTER VISION

Meta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materials

Yawar Siddiqui, Tom Monnier, Filippos Kokkinos, Mahendra Kariya, Yanir Kleiman, Emilien Garreau, Oran Gafni, Natalia Neverova, Andrea Vedaldi, Roman Shapovalov, David Novotny

July 02, 2024

July 02, 2024

GRAPHICS

COMPUTER VISION

Meta 3D Gen

Raphael Bensadoun, Tom Monnier, Yanir Kleiman, Filippos Kokkinos, Yawar Siddiqui, Mahendra Kariya, Omri Harosh, Roman Shapovalov, Emilien Garreau, Animesh Karnewar, Ang Cao, Idan Azuri, Iurii Makarov, Eric-Tuan Le, Antoine Toisoul, David Novotny, Oran Gafni, Natalia Neverova, Andrea Vedaldi

July 02, 2024

July 02, 2024

GRAPHICS

COMPUTER VISION

Meta 3D TextureGen: Fast and Consistent Texture Generation for 3D Objects

Raphael Bensadoun, Yanir Kleiman, Idan Azuri, Omri Harosh, Andrea Vedaldi, Natalia Neverova, Oran Gafni

July 02, 2024

June 20, 2024

COMPUTER VISION

ICON: Incremental CONfidence for Joint Pose and Radiance Field Optimization

Weiyao Wang, Pierre Gleize, Hao Tang, Xingyu Chen, Kevin Liang, Matt Feiszli

June 20, 2024

Help Us Pioneer The Future of AI

We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.