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GeoCV 2027
Geospatial imagery plays an increasingly important role in environmental monitoring, climate resilience, agriculture, urban planning, disaster response, and humanitarian action. At the same time, imagery collected from satellites, aircraft, drones, and ground platforms presents fundamental computer vision challenges, including heterogeneous sensing modalities, large variations in scale and resolution, limited or noisy annotations, spatial and temporal domain shifts, and the need for reliable inference in open-world settings. GeoCV brings together the computer vision and geospatial imaging communities to advance methods for scalable, robust, and responsible analysis of Earth-observation data. The workshop provides a forum for researchers developing new computer vision and machine learning methods to engage directly with geospatial researchers addressing challenging real-world problems.
GeoCV 2027 builds on two successful prior editions at WACV. GeoCV 2025 was a full-day workshop featuring five keynote talks, 20 archival papers, nine extended abstracts, approximately 30 posters, and strong attendance throughout the day. GeoCV 2026 continued this momentum with three keynote talks, 16 papers, three extended abstracts, additional invited contributions, and once again drew a full room. The third edition will highlight emerging directions including multimodal geospatial foundation models, vision-language models, language-guided and agentic GeoAI, label-efficient learning, cross-sensor and cross-region generalization, multi-sensor fusion, and trustworthy geospatial AI, while continuing to emphasize impactful applications across Earth observation.
Call for Papers
Call for Papers
We invite authors to submit high-quality papers on computer vision and image analysis for geospatial imaging. Submitted manuscripts will be peer-reviewed, and refereed for originality, presentation, empirical results and overall quality. In addition to papers focused on algorithmic novelty, we also encourage papers that demonstrate effective deployment of recent computer vision paradigms to compelling geospatial imaging applications.
Topics of interest include (but are not limited to):
Geospatial foundation models, large vision models, and multimodal or vision-language models
Agentic and language-guided GeoAI, spatial reasoning, and interactive Earth-observation systems
Self-supervised, weakly supervised, few-shot, active, and other label-efficient learning
Domain adaptation and generalization, open-world recognition, out-of-distribution detection, and trustworthy geospatial AI
Multi-sensor and multi-temporal fusion across optical, SAR, LiDAR, thermal, and hyperspectral data
Generative modeling and computer vision methods including super-resolution, reconstruction, segmentation, detection, and change analysis
Applications in environmental and biodiversity monitoring, agriculture, climate, disaster response, urban systems, humanitarian applications, and sustainable development
Submission Types
Regular Research Papers
Regular papers should present original research and will undergo peer review. Papers must be 5–8 pages, excluding references, and follow the WACV 2027 formatting guidelines. Accepted regular papers that are presented at the workshop will be included in the WACV 2027 Workshop Proceedings.
Manuscript Submission
Manuscript Submission
Submissions will be handled through OpenReview.
Submission site for Regular Research Papers: Click here
Authors should follow the WACV 2027 formatting and submission requirements for regular workshop papers. Additional submission instructions will be posted here as they become available.
Organizers
Organizers
Saurabh Prasad
University of Houston
Jocelyn Chanussot
INRIA
Claudia Paris
University of Twente
Biplab Banerjee
Indian Institute of Technology, Bombay
Danfeng Hong
Southeast University
Invited Speakers
Invited Speakers
Chen Chen
University of Central Florida
Chen Chen is an Associate Professor of Computer Science at the University of Central Florida. He received his Ph.D. in Electrical Engineering from the University of Texas at Dallas in 2016, where he received the David Daniel Fellowship for Best Doctoral Dissertation. His research interests include computer vision, efficient deep learning, and federated learning, with applications to resource-aware machine vision, large-scale camera networks, and the Internet of Things.
Alina Zare
University of Florida
Alina Zare is a Professor of Electrical and Computer Engineering at the University of Florida and Director of the Artificial Intelligence and Informatics Research Institute. Her research focuses on machine learning and AI for automated understanding of complex data and imagery, with applications including hyperspectral imaging, remote sensing, plant phenotyping, sonar, LiDAR, ground-penetrating radar, and target and hazard detection.
Important Dates
Regular Paper Track (Archival):
Important Dates
Regular Paper Track (Archival):
Regular paper submission: October 14, 2026 AOE
Notification of acceptance: November 2, 2026
Camera-ready deadline: November 20
GeoCV 2027 Workshop: January 4 or 5, 2027
Program Committee
Program Committee
To be anounced soon
Workshop Program
Workshop Program
Workshop program will be announced after conclusion of the peer-review period.
Past Workshops:
2nd Edition of GeoCV @ WACV 2026:
The program for the workshop is now available here, and the workshop proceedings are now available here: https://openaccess.thecvf.com/WACV2025_workshops/GeoCV
1st Edition of GeoCV @ WACV 2025:
The program for the workshop is now available here, and the workshop proceedings are now available here: https://openaccess.thecvf.com/WACV2025_workshops/GeoCV
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