CALL FOR PARTICIPANTS & PAPERS

EarthVision 2023 – Large Scale Computer Vision for Remote Sensing Imagery Workshop 

in conjunction with CVPR 2023, June 2023, Vancouver, Canada. 

Website: https://www.grss-ieee.org/earthvision2023/

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

• Evaluating models using unlabeled data

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

• 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

• 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 9, 2023

Notification of acceptance: March 30, 2023

Camera-ready paper: April 6, 2023

Workshop (full day): June 18, 2023

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 2023 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

Nathan Jacobs, Washington University in St. Louis, USA

Loïc Landrieu, IGN, France

Charlotte Pelletier, UBS Vannes, France

Hannah Kerner, Arizona State University, USA

Beth Tellman, University of Arizona, USA

CHALLENGE

EarthVision 2023 will feature the African Biomass Challenge with the goal to accurately estimate aboveground biomass in different cocoa plantations in Côte d'Ivoire. The dataset consists of ESA Sentinel-2 images, NASA GEDI data and ground truth biomass. All AI practitioners, experts and enthusiasts are invited to take part in the competition organized on Zindi.

SPONSORING

The event is co-organized by the Image Analysis and Data Fusion Technical Committee of the IEEE-GRSS, and it is sponsored by Blacksky, Exolabs, Picterra, and Kitware.

Website: https://www.grss-ieee.org/earthvision2023/