EARTHVISION 2022
July 19th/20th, New Orleans, Louisiana - hybrid/virtual
in conjuction with the Computer Vision and Pattern Recognition (CVPR) 2022 Conference
Aims and Scope
Earth Observation (EO)/Remote Sensing is an ever-growing field of investigation where computer vision, machine learning, and signal/image processing meet. The general objective of the domain is to provide large-scale, homogeneous information about processes occurring at the surface of the Earth exploiting data collected by airborne and spaceborne sensors. Earth Observation covers a broad range of tasks, ranging from detection to registration, data mining, multi-sensor, multi-resolution, multi-temporal, and multi-modality fusion, and regression, to name just a few. It is motivated by numerous applications such as location-based services, online mapping services, large-scale surveillance, 3D urban modelling, navigation systems, natural hazard forecast and response, climate change monitoring, virtual habitat modelling, etc. The sheer amount of data calls for highly automated scene interpretation workflows. Earth Observation and in particular the analysis of spaceborne data directly connects to 34 indicators out of 40 (29 targets and 11 goals) of the Sustainable Development Goals defined by the United Nations. The aim of EarthVision to advance the state of the art in machine learning-based analysis of remote sensing data is thus of high relevance. It also connects to other immediate societal challenges such as monitoring of forest fires and other natural hazards, urban growth, deforestation, and climate change. Submissions are invited from all areas of computer vision and image analysis relevant for, or applied to, environmental remote sensing. Topics of interest include, but are not limited to:
- Super-resolution in the spectral and spatial domain
- Hyperspectral and multispectral image processing
- 3D reconstruction from aerial optical and LiDAR acquisitions
- Feature extraction and learning from spatio-temporal data
- Semantic classification 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
- 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.
All manuscripts will be subject to a double-blind review process. Accepted EARTHVISION papers will be included in the CVPR2021 workshop proceedings (published open access on the Computer Vision Foundation website) and submitted to IEEE for publication in IEEE Xplore. Publication in IEEE Xplore will be granted only if the paper meets IEEE publication policies and procedures.
Important Dates
| March 9, 2022 | Full paper submission | 11:59 pm |
| April 1, 2022 | Decision notification to authors | |
| April 8, 2022 | Camera-ready paper | |
| June 19 or 20, 2022 | Workshop | Full day |
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
- Naoto Yokoya, Univ. of Tokyo & RIKEN, Japan
- Nathan Jacobs, Univ. of Kentucky, USA
- Fabio Pacifici, Maxar, USA
- Mariko Burgin, NASA JPL, USA
- Loïc Landrieu, IGN, France
- Charlotte Pelletier, UBS Vannes, France
Challenges
We are pleased to announce that EarthVision 2022 will feature the upcoming SpaceNet 8 Challenge. Details will be announced soon. Stay tuned!
Sponsors
Affiliations
Submissions
1. Prepare the anonymous, 8-page (references excluded) submission using the ev2022-template and following the PaperForReview.
2. Submit on cmt3.research.microsoft.com/EARTHVISION2022.
Policies
A complete paper should be submitted using the EarthVision templates provided above.
Reviewing is double blind, i.e. authors do not know the names of the reviewers and reviewers do not know the names of the authors. Please read Section 1.7 of the example paper earthvision.pdf for detailed instructions on how to preserve anonymity. Avoid providing acknowledgments or links that may identify the authors.
Papers are to be submitted using the dedicated submission platform: cmt3.research.microsoft.com/EARTHVISION2022. The submission deadline is strict.
By submitting a manuscript, the authors guarantee that it has not been previously published or accepted for publication in a substantially similar form. CVPR rules regarding plagiarism, double submission, etc. apply."
CVPR 2022
CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.
