CALL FOR PAPERS

EarthVision 2024 – Large Scale Computer Vision for Remote Sensing Imagery Workshop 

in conjunction with CVPR 2024, June 2024, Seattle, USA. 

Website: https://www.grss-ieee.org/events/earthvision-2024/

AIMS AND SCOPE

Earth Observation (EO) and remote sensing are fast growing fields of investigation where computer vision, machine learning, and signal/image processing meet. The general objective of EO is to provide large-scale and consistent information about processes occurring at the surface of the Earth by exploiting data collected by airborne and spaceborne sensors. EO covers a broad range of tasks, from detection to registration, data mining, and multi-sensor, multi-resolution, multi-temporal, multi-modal fusion and regression, to name just a few. It serves numerous  applications such as location-based services, online mapping, large-scale surveillance, 3D urban modeling, navigation systems, natural hazard forecast and response, climate change monitoring, virtual habitat modeling, food security, etc. The sheer amount of data calls for highly automated scene interpretation workflows. 

The Earthvision workshop, held for its seventh edition at the CVPR 2023, aims at fostering collaboration between the computer vision, machine learning, and the remote sensing communities to boost automated analysis of EO data. EarthVision will strive to build cooperation within the CVPR community for this highly challenging and quickly evolving field with a significant impact on society, economy, industry, and the environment. 

We invite contributions in the fields of (not exhaustive list):

• Super-resolution in the spectral and spatial domain

• Hyperspectral and multispectral image processing

• Reconstruction and segmentation of optical and LiDAR 3D point clouds

• Feature extraction and learning from spatio-temporal data 

• Analysis  of UAV / aerial and satellite images and videos

• Deep learning tailored for large-scale Earth Observation

• Domain adaptation, concept drift, and the detection of out-of-distribution data

• Data-centric machine learning

• Evaluating models using unlabeled data

• Self-, weakly, and unsupervised approaches for learning with spatial data

• Foundation models and representation learning in the context of EO

• Human-in-the-loop and active learning

• Multi-resolution, multi-temporal, multi-sensor, multi-modal processing

• Fusion of machine learning and physical models

• Explainable and interpretable machine learning in Earth Observation applications

• Uncertainty quantification of machine-learning based prediction from EO data

• Applications for climate change, sustainable development goals, and geoscience

• Public benchmark datasets: training data standards, testing & evaluation metrics, as well as open source research and development.

IMPORTANT DATES

Full paper submission: March 8, 2024

Notification of acceptance: April 5, 2024

Camera-ready paper: April 12, 2024

Workshop (full day): June 17/18, 2024

SUBMISSION GUIDELINES

A complete paper should be submitted using the EarthVision templates provided on the workshop website. The paper length must not exceed 8 pages (excluding references) and formatting follows CVPR 2024 instructions. All manuscripts will be subject to a double-blind review process, i.e. authors must not identify themselves on the submitted papers. The reviewing process is single-stage, meaning that there will not be rebuttals to reviewers.

Papers are to be submitted using the dedicated submission platform on the workshop website. By submitting a manuscript, the authors guarantee that it has not been previously published or accepted for publication in substantially similar form. CVPR rules regarding plagiarism, double submission, etc. apply.  

WORKSHOP ORGANIZERS

Ronny Hänsch, German Aerospace Center, Germany

Devis Tuia, EPFL, Switzerland

Jan Dirk Wegner, University of Zurich & ETH Zurich, Switzerland

Bertrand Le Saux, ESA/ESRIN, Italy

Loïc Landrieu, IGN, France

Charlotte Pelletier, UBS Vannes, France

Hannah Kerner, Arizona State University, USA

SPONSORING

The event is co-organized by the Image Analysis and Data Fusion Technical Committee of the IEEE-GRSS, and it is sponsored by Exolabs. If your organization is interested to co-sponsor the event, please don’t hesitate to reach out.

Website: https://www.grss-ieee.org/events/earthvision-2024/