Drone-Based Wildlife Monitoring

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Overview

The field uses drone imagery and video to detect and count wildlife, follow individuals, classify species or life stages, and map animals for ecological surveys. Approaches include object detection and point-supervised density estimation, multi-object tracking, RGB–thermal fusion, 3D reconstruction, and autonomous drone coordination. Benchmarks span aerial survey datasets with small or rare animals, dense groups, and monocular 3D scenes, while geospatial priors and active learning aim to reduce annotation effort. A central tension is obtaining reliable measurements across species and field conditions while addressing limited labels, uncertain depth, and the risk that close or repeated flights disturb animals.

Latest papers

CardsList

13 papers1 paper in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

  1. trACT: temporal revelation Airborne Camera Trap

    Oct 7, 2026Oliver Bimber, Rakesh John Amala Arokia Nathan, Mohamed Youssef +3Aerial RoboticsDrone-Based Wildlife Monitoring

    Department of Computer Science, Johannes Kepler University Linz, Austria · Institute of Space Research, German Aerospace Center, Berlin, Germany · BOKU University, Institute of Wildlife Biology and Game Management,, Vienna, Austria +1

  2. Re-engineering SORT-based algorithms for low-cost small object tracking from omnidirectional footage

    Sep 7, 2026Xin Shu, Meegan Gower, Yvonne Buckley +1Visual Object TrackingDrone-Based Wildlife Monitoring

    Sigmedia Group, Electronic and Electrical Engineering, Trinity College Dublin · School of Zoology, Trinity College Dublin

  3. When One Modality Is Not Enough: Multimodal Sex and Life-Stage Classification of Red Deer from Aerial RGB-Thermal Video

    Aug 7, 2026Hugo Markoff, Christoph Praschl, Ivan Ludoški +3Multimodal ClassificationDrone-Based Wildlife Monitoring

    Aalborg University, Department of Chemistry and Bioscience, Aalborg, Denmark · University of Applied Sciences Upper Austria, Hagenberg, Austria · University of Novi Sad, Faculty of Agriculture, Novi Sad, Serbia +1

  4. Oh Deer, How Should I Handle This? Seasonal Priors for Selective Wildlife Annotation and Classification

    Aug 3, 2026Hugo Markoff, Christoph Praschl, Anton Hjalte Jørgensen +5Selective PredictionHuman-in-the-Loop Annotation

    Aalborg University, Department of Chemistry and Bioscience, Aalborg, Denmark · University of Applied Sciences Upper Austria, Hagenberg, Austria · Massachusetts Institute of Technology, Cambridge, MA, USA

  5. Autonomous UAV Navigation for Individual Wildlife Re-Identification

    Jun 30, 2026Claire Sun, Tanya Berger-Wolf, Jenna KlineAnimal Re-IdentificationUAV Navigation

    The Ohio State University

  6. WildBox: A Dataset and Benchmark for Aerial Monocular 3D Detection of African Savanna Wildlife

    Jun 19, 2026Vandita Shukla, Kilian Meier, Lucie Laporte-Devylder +6Monocular Depth Estimation3D Object Detection

    13D Optical Metrology Unit, Fondazione Bruno Kessler, Trento, Italy · 2Computer Vision and Machine Learning Systems group, Institute for Geoinformatics, University of Muenster, Muenster, Germany · School of Civil, Aerospace and Design Engineering, University of Bristol, Bristol, UK +6

  7. Overhead Wildlife Locator (OWL): Benchmarking Weakly Supervised Learning for Aerial Wildlife Surveys

    Jun 11, 2026Isai Daniel Chacón, Zhongqi Miao, Bruno Demuro +9Remote Sensing Image UnderstandingWeakly Supervised Learning

    Microsoft AI for Good Lab, Redmond, WA, USA · Center for Research and Formation in Artificial Intelligence (Cinfonia), Universidad de los Andes, Bogotá, Colombia · Conservation X Labs, Washington, D.C., USA +3

  8. Disturbance-Aware Aerial Robotics for Ethical Wildlife Monitoring

    Jun 6, 2026Mahmut Osmanovic, Isac Paulsson, Teddy LazebnikRL for RoboticsAerial Robotics

    Department of Computing, Jonkoping University, Jonkoping, Sweden · Department of Information Systems, University of Haifa, Haifa, Israel

  9. FAIR^2 Drones: An AI-Ready Standard for Cross-Domain Wildlife Drone Datasets

    May 29, 2026Jenna Kline, Kilian Meier, Vandita Shukla +14Drone-Based Wildlife MonitoringWildlife Monitoring

    The Ohio State University, Department of Computer Science and Engineering, Columbus, OH, USA · School of Civil, Aerospace and Design Engineering, University of Bristol, Bristol, United Kingdom · 33D Optical Metrology (3DOM), Fondazione Bruno Kessler (FBK), Trento, Italy +7

  10. WildLIFT: Lifting monocular drone video to 3D for species-agnostic wildlife monitoring

    Apr 27, 2026Vandita Shukla, Fabio Remondino, Blair Costelloe +13D Object DetectionDrone-Based Wildlife Monitoring

    13D Optical Metrology, Fondazione Bruno Kessler, Trento, Italy. · Computer Vision and Machine Learning Systems Group, University of Muenster, Muenster, Germany. · Department of Collective Behaviour, Max Planck Institute of Animal Behaviour, Konstanz, Germany. +2

  11. RareSpot+: A Benchmark, Model, and Active Learning Framework for Small and Rare Wildlife in Aerial Imagery

    Apr 21, 2026Bowen Zhang, Jesse T. Boulerice, Charvi Mendiratta +4Remote Sensing Small Object DetectionSmall Object Detection

    University of California, Santa Barbara, 93106, California, United States of America. · 2Smithsonian National Zoo and Conservation Biology Institute, 20008, Washington, DC, United States of America. · 3Stanford University, 94305, California, United States of America. +1

  12. KAMERA: Enhancing Aerial Surveys of Ice-associated Seals in Arctic Environments

    Sep 23, 2025Adam Romlein, Benjamin X. Hou, Yuval Boss +5Multispectral Object DetectionRemote Sensing

    Kitware, Inc., USA · NOAA NMFS AFSC MML, USA · CICOES, University of Washington, USA

  13. Decentralized Vision-Based Autonomous Aerial Wildlife Monitoring

    Aug 20, 2025Makram Chahine, William Yang, Alaa Maalouf +6Multi-Robot CoordinationDrone-Based Wildlife Monitoring

    Project CETI, New York 10003, NY, USA · CSAIL MIT, Cambridge MA 02139, USA · SEAS Harvard University, Boston MA 02134, USA