mlsanityData to 7 Oct 2026

DrIFT: Autonomous Drone Dataset with Integrated Real and Synthetic Data, Flexible Views, and Transformed Domains

arXiv 2412.04789 ↗First posted 6 Dec 2024cs.CVcited by 6

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Abstract (arXiv)

Dependable visual drone detection is crucial for the secure integration of drones into the airspace. However, drone detection accuracy is significantly affected by domain shifts due to environmental changes, varied points of view, and background shifts. To address these challenges, we present the DrIFT dataset, specifically developed for visual drone detection under domain shifts. DrIFT includes fourteen distinct domains, each characterized by shifts in point of view, synthetic-to-real data, season, and adverse weather. DrIFT uniquely emphasizes background shift by providing background segmentation maps to enable background-wise metrics and evaluation. Our new uncertainty estimation metric, MCDO-map, features lower postprocessing complexity, surpassing traditional methods. We use the MCDO-map in our uncertainty-aware unsupervised domain adaptation method, demonstrating superior performance to SOTA unsupervised domain adaptation techniques. The dataset is available at: https://github.com/CARG-uOttawa/DrIFT.git.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 36 of its 69 references that are in the map. First posted on arXiv 6 Dec 2024.

Builds on

36 of 69 references.

References · 36

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24 more
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  2. 2018Model Adaptation with Synthetic and Real Data for Semantic Dense Foggy Scene Understandingcited by 98
  3. 2020Multivariate Confidence Calibration for Object Detectioncited by 98
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 3.

6 papers.

  1. 2025Drone Detection with Event Camerascited by 9
  2. 2025UAV-MM3D: A Large-Scale Synthetic Benchmark for 3D Perception of Unmanned Aerial Vehicles with Multi-Modal Datacited by 3
  3. 2025LAA3D: A Benchmark of Detecting and Tracking Low-Altitude Aircraft in 3D Spacecited by 0
  4. 2026Visual Marker Search for Autonomous Drone Landing in Diverse Urban Environmentscited by 0
  5. 2026Beyond Clear Skies: Synthetic Seasonal and Weather Variations for Real-World Drone Detectioncited by 0
  6. 2026DroneGround: Open-Vocabulary Drone Payload Characterization Using Synthetic Data and Grounded Vision-Language Modelscited by 0