首个细粒度鸟类行为视频数据集，助力物种识别与行为分析
Visual WetlandBirds Dataset: Bird Species Identification and Behavior Recognition in Videos
- 构建178段西班牙湿地鸟类视频，涵盖13种鸟、7类行为
- 提供细粒度标注，支持深度学习模型训练与评估
- 适合计算机视觉与生物多样性研究者使用
当前生物多样性丧失危机使动物监测成为重要研究领域。监测数据可为保护决策提供关键信息。尽管数据至关重要，现有视频数据集仍严重缺乏，尤其缺少鸟类行为的详细标注。为此，本研究提出首个专用于鸟类行为检测与物种分类的细粒度视频数据集。该数据集包含178段西班牙湿地拍摄的视频，涵盖13种不同鸟类，记录7种行为类别。同时，我们基于先进模型在两个任务上提供了基线结果：鸟类行为识别与物种分类，推动深度学习在鸟类视觉理解中的应用。
原文摘要 · Abstract (English)
The current biodiversity loss crisis makes animal monitoring a relevant field of study. In light of this, data collected through monitoring can provide essential insights, and information for decision-making aimed at preserving global biodiversity. Despite the importance of such data, there is a notable scarcity of datasets featuring videos of birds, and none of the existing datasets offer detailed annotations of bird behaviors in video format. In response to this gap, our study introduces the first fine-grained video dataset specifically designed for bird behavior detection and species classification. This dataset addresses the need for comprehensive bird video datasets and provides detailed data on bird actions, facilitating the development of deep learning models to recognize these, similar to the advancements made in human action recognition. The proposed dataset comprises 178 videos recorded in Spanish wetlands, capturing 13 different bird species performing 7 distinct behavior classes. In addition, we also present baseline results using state of the art models on two tasks: bird behavior recognition and species classification.
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