We present the PanAf20K dataset, the largest and most diverse open-access annotated video dataset of great apes in their natural environment. It comprises more than 7 million frames across ~20,000 camera trap videos of chimpanzees and gorillas collected at 14 field sites in tropical Africa as part of the Pan African Programme: The Cultured Chimpanzee. The footage is accompanied by a rich set of annotations and benchmarks making it suitable for training and testing a variety of challenging and ecologically important computer vision tasks including ape detection and behaviour recognition. Furthering AI analysis of camera trap information is critical given the International Union for Conservation of Nature now lists all species in the great ape family as either Endangered or Critically Endangered. We hope the dataset can form a solid basis for engagement of the AI community to improve performance, efficiency, and result interpretation in order to support assessments of great ape presence, abundance, distribution, and behaviour and thereby aid conservation efforts.

翻译：我们提出PanAf20K数据集，这是目前规模最大、多样性最丰富的开放获取标注视频数据集，专门记录自然环境中大型猿类的活动。该数据集包含来自热带非洲14个野外站点的约20,000个红外相机视频片段，涵盖超过700万帧黑猩猩与大猩猩影像，这些影像资料源自"泛非洲计划：文化黑猩猩"项目。所有视频均附有丰富的标注信息与基准测试，适用于训练和测试包括猿类检测与行为识别在内的多种具有挑战性且生态重要性的计算机视觉任务。鉴于国际自然保护联盟已将全部大型猿类物种列为濒危或极危状态，推进人工智能对红外相机信息的分析至关重要。我们期望该数据集能为人工智能社区的参与奠定坚实基础，通过提升性能、效率及结果解读能力，支持对大型猿类存在性、丰度、分布及行为的研究，进而助力保护工作。