FBD-SV-2024: Flying Bird Object Detection Dataset in Surveillance Video
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Abstract (arXiv)
A Flying Bird Dataset for Surveillance Videos (FBD-SV-2024) is introduced and tailored for the development and performance evaluation of flying bird detection algorithms in surveillance videos. This dataset comprises 483 video clips, amounting to 28,694 frames in total. Among them, 23,833 frames contain 28,366 instances of flying birds. The proposed dataset of flying birds in surveillance videos is collected from realistic surveillance scenarios, where the birds exhibit characteristics such as inconspicuous features in single frames (in some instances), generally small sizes, and shape variability during flight. These attributes pose challenges that need to be addressed when developing flying bird detection methods for surveillance videos. Finally, advanced (video) object detection algorithms were selected for experimentation on the proposed dataset, and the results demonstrated that this dataset remains challenging for the algorithms above. The FBD-SV-2024 is now publicly available: Please visit https://github.com/Ziwei89/FBD-SV-2024_github for the dataset download link and related processing scripts.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 14 of its 31 references that are in the map. First posted on arXiv 31 Aug 2024.
Builds on
14 of 31 references.
References · 14
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Built on by
Citing papers per year: 2024: 1; 2025: 3; 2026: 1.
5 papers.
- 2025MVA 2025 Small Multi-Object Tracking for Spotting Birds Challenge: Dataset, Methods, and Resultscited by 2
- 2024Self-Paced Learning Strategy with Easy Sample Prior Based on Confidence for the Flying Bird Object Detection Model Trainingcited by 1
- 2025Co-Paced Learning Strategy Based on Confidence for Flying Bird Object Detection Model Trainingcited by 0
- 2025Not All Birds Look The Same: Identity-Preserving Generation For Birdscited by 0
- 2026Teach a Molmo2Fish: Towards interactive fish tracking with natural language guidancecited by 0
- 2026Teach a Molmo2Fish: Towards interactive fish tracking with natural language guidance19 Aug 2026
- 2025Not All Birds Look The Same: Identity-Preserving Generation For Birds4 Dec 2025
- 2025MVA 2025 Small Multi-Object Tracking for Spotting Birds Challenge: Dataset, Methods, and Results17 Jul 2025
- 2025Co-Paced Learning Strategy Based on Confidence for Flying Bird Object Detection Model Training21 Jan 2025
- 2024Self-Paced Learning Strategy with Easy Sample Prior Based on Confidence for the Flying Bird Object Detection Model Training9 Dec 2024