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

March 20, 2024

COMPUTER VISION

SceneScript: Reconstructing Scenes With An Autoregressive Structured Language Model

Armen Avetisyan, Chris Xie, Henry Howard-Jenkins, Tsun-Yi Yang, Samir Aroudj, Suvam Patra, Fuyang Zhang, Duncan Frost, Luke Holland, Campbell Orme, Jakob Julian Engel, Edward Miller, Richard Newcombe, Vasileios Balntas

March 20, 2024

February 13, 2024

GRAPHICS

COMPUTER VISION

IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation

Luke Melas-Kyriazi, Iro Laina, Christian Rupprecht, Natalia Neverova, Andrea Vedaldi, Oran Gafni, Filippos Kokkinos

February 13, 2024

January 25, 2024

COMPUTER VISION

LRR: Language-Driven Resamplable Continuous Representation against Adversarial Tracking Attacks

Felix Xu, Di Lin, Jianjun Zhao, Jianlang Chen, Lei Ma, Qing Guo, Wei Feng, Xuhong Ren

January 25, 2024

December 08, 2023

COMPUTER VISION

Learning Fine-grained View-Invariant Representations from Unpaired Ego-Exo Videos via Temporal Alignment

Sherry Xue, Kristen Grauman

December 08, 2023

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.