The 2026 Workshop on Advances in Drone Vision (ADV 2026) aims to bring together leading researchers and practitioners from academia and industry to explore cutting-edge developments in drone-based computer vision. As drones become increasingly integral to sectors such as agriculture, logistics, infrastructure monitoring, disaster response, and environmental surveillance, computer vision has emerged as the key enabler of autonomy and intelligence in aerial systems.

ADV 2026 will serve as a platform to present and discuss innovative methodologies in vision-based perception for drones, including onboard processing, anomaly detection, aerial image segmentation, and more. The workshop seeks to foster interdisciplinary collaboration and advance the capabilities of intelligent, autonomous aerial platforms.

Submission Guidelines

All submissions must be original and not under review by any other journal or conference. Submissions must be made electronically via EasyChair. Authors must format their papers according to the CEUR-WS guidelines.

Authors are invited to submit original contributions in the following formats:

• Regular Papers: up to 12 pages, including references, presenting completed work with substantial technical content.
• Short Papers: Up to 8 pages, including references, reporting preliminary results or ongoing research.

Each paper will undergo a single-blind peer review process and will be evaluated based on originality, technical quality, significance, clarity, and relevance to the workshop topics.

Upon acceptance, at least one author must register for ADV 2026, attend the workshop, and present the paper.

Important Dates

• Paper submission deadline: April 13, 2025
• Notification of acceptance: May 11, 2025
• Camera-ready submission: May 18, 2025

List of Topics

We invite contributions on a wide range of topics related to computer vision for drones, including but not limited to:

• Object detection, tracking, and recognition from aerial imagery
• Semantic and instance segmentation for aerial vision
• Scene understanding and 3D reconstruction from drone-captured data
• Multimodal fusion for aerial perception
• Event-based vision for high-speed drone applications
• Real-time localization, mapping, and environment representation
• Vision-based trajectory planning and obstacle avoidance
• Energy-efficient perception for extended drone operations
• Swarm intelligence and collaborative drone vision
• AI-driven applications for disaster response and environmental monitoring
• Drone vision for smart cities and infrastructure assessment
• Assistive drones for healthcare and search-and-rescue missions
• Edge AI and real-time onboard processing for drones
• Lightweight deep learning models for resource-constrained UAVs
• Secure and privacy-preserving drone vision systems
• Drone vision in precision agriculture and environmental sustainability
• Surveillance and security applications leveraging aerial vision
• Autonomous inspection of industrial and energy infrastructure
• AI-powered delivery and logistics with drone-based perception

Committees

Program Committee

• Danilo Avola
• Daniele Pannone
• Angelo Ciaramella
• Ciro Russo
• Davide Moroni
• Paolo Soda
• Gian Luca Foresti
• Mara Pistellato
• Angelo Cardellicchio
• Mario Vento
• Carmen Bisogni
• Pietro Pala
• Ivan Scagnetto
• Vito Renò

Organizing Committee

• Gennaro Vessio, University of Bari Aldo Moro
• Giovanna Castellano, University of Bari Aldo Moro
• Pasquale De Marinis, University of Bari Aldo Moro
• Alessia Saggese, University of Salerno
• Federico Becattini, University of Siena

Publication

All accepted papers will be submitted for publication in the CEUR Workshop Proceedings.

Venue

TBA

Contact

All questions about submissions should be directed to:

Gennaro Vessio, University of Bari Aldo Moro, Email: gennaro.vessio@uniba.it