A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2023; you can also visit the original URL.
The file type is application/pdf
.
Towards Large-Scale Small Object Detection: Survey and Benchmarks
[article]
2023
accepted
With the rise of deep convolutional neural networks, object detection has achieved prominent advances in past years. However, such prosperity could not camouflage the unsatisfactory situation of Small Object Detection (SOD), one of the notoriously challenging tasks in computer vision, owing to the poor visual appearance and noisy representation caused by the intrinsic structure of small targets. In addition, large-scale dataset for benchmarking small object detection methods remains a
doi:10.1109/tpami.2023.3290594
pmid:37384469
arXiv:2207.14096v4
fatcat:ip2qiredsfh2ffqbxyq6pgl2dm