Detection and classification of objects in overhead images are two important and challenging problems in computer vision.
Among various research areas in this domain, the task of fine-grained classification of objects in overhead images has become ubiquitous in diverse real-world applications, due to recent advances in high-resolution satellite and airborne imaging systems.
The small inter-class variations and the large intra class variations caused by the fine grained nature make it a challenging task, especially in low-resource cases.
In this paper, we introduce COFGA a new open dataset for the advancement of fine-grained classification research.
cofga: A Dataset for Fine Grained Classification of Objects from Aerial Imagery · Around
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