Camera Traps, AI, and Ecology - International Workshop Archive

We invite you to submit extended abstracts (4 pages, excl. references) and full papers (6 pages, excl. references) related to AI image analysis of camera trap data for wildlife monitoring and conservation. The review process will be single-blind, and there will be at least two independent reviewers evaluating each paper. Selected best papers will be invited to submit an extended version of their paper to a Special Issue in the IET Computer Vision Journal. Further information on the scope of papers is given below as well as in this Call for papers!

Author instructions: For preparing your paper, please also stick to the rules and formats provided by the following templates: LaTeX | Word

Paper submission via CMT: https://cmt3.research.microsoft.com/CamTrapAI2025

(The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.)

All papers must contain original research that has not been published before and has not been submitted (simultaneously) to another workshop, conference, or journal.

However, we specifically encourage to submit early findings that might be extended for future submission to another venue after the workshop.

The scope of this workshop is to bring together people analyzing camera trap data with artificial intelligence (AI) support. We want to discuss current open challenges and the latest algorithmic solutions to related problems. Besides computer scientists working on new computer vision and machine learning methods, we also address ecologists using existing AI tools to tackle open problems and answer specific questions within their application domain. Hence, we encourage especially interdisciplinary teams working at the intersection of AI and ecology to submit the results of their recent work.

Paper submission is open for a broad range of topics and application domains, including but not limited to:

Analyzing camera trap data or other related ecological vision datasets (images, image sequences, or videos)
Camera traps in the wild or in controlled environments like a Zoo,
Observations of birds and bugs, mammals and moths, spiders and snakes, etc.,
Investigating images and videos from insect monitoring cameras (Lepidoptera, pollinators, anthropods, etc.),
Maritime and freshwater applications by studying underwater imagery of fish and other aquatic animals,
Animal detection and movement tracking of groups and individuals,
Video recognition of animal behavior analysis,
Identification of species, individuals, and morphological traits (in images or videos)
Fine-grained visual categorization approaches and related recognition tasks at subordinate levels,
Animal pose estimation in still images and video footage,
Applying AI methods to camera trap data for answering ecological questions,
New ecological questions or important open problems that can’t be solved with current AI approaches.

We also invite papers showing preliminary results if the paper contribution is clearly outlined and inspects one of the following topics:

A new AI method that shows promising results on camera trap or other ecology datasets.
A new ecological question or an open problem that can barely be addressed with existing AI techniques and inspires the development of advanced algorithms.
A new dataset with a description of the specific tasks and challenges, that require the development of new AI methods.