Survey of small object detection using transformers
Survey of small object detection using transformers
Transformers in Small Object Detection: A Benchmark and Survey of State-of-the-Art
arXiv paper abstract https://arxiv.org/abs/2309.04902
arXiv PDF paper https://arxiv.org/pdf/2309.04902.pdf
GitHub of papers with source https://github.com/arekavandi/Transformer-SOD
Transformers have rapidly gained popularity in computer vision, especially in the field of object recognition and detection.
… aims to explore the performance benefits offered by such extensive networks and identify potential reasons for their SOD superiority.
Small objects have been identified as one of the most challenging object types in detection frameworks due to their low visibility.
… This survey presents a taxonomy of over 60 research studies on developed transformers for the task of SOD, spanning the years 2020 to 2023.
These studies encompass a variety of detection applications, including small object detection in generic images, aerial images, medical images, active millimeter images, underwater images, and videos.
… present a list of 12 large-scale datasets suitable for SOD that were overlooked in previous studies and compare the performance of the reviewed studies …
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