Deep learning-based detection from the perspective of small or tiny objects: A survey
作者：
Highlights：
• Summarize the 30 datasets about small or tiny objects.
• Provide definitions of small/tiny objects based on different application scenarios.
• Systematically review small/tiny object detection techniques from seven aspects.
• Present the evaluation results of different methods for small/tiny object detection.
• Discuss future research directions of small/tiny object detection.
摘要
•Summarize the 30 datasets about small or tiny objects.•Provide definitions of small/tiny objects based on different application scenarios.•Systematically review small/tiny object detection techniques from seven aspects.•Present the evaluation results of different methods for small/tiny object detection.•Discuss future research directions of small/tiny object detection.
论文关键词：Object detection,Small or tiny objects,Deep learning,Datasets,Convolutional neural networks
论文评审过程：Received 6 December 2021, Revised 19 March 2022, Accepted 4 May 2022, Available online 10 May 2022, Version of Record 16 May 2022.
论文官网地址：https://doi.org/10.1016/j.imavis.2022.104471
