Survey of fine-grained image analysis using deep learning
Survey of fine-grained image analysis using deep learning
Fine-Grained Image Analysis with Deep Learning: A Survey
arXiv paper abstract https://arxiv.org/abs/2111.06119v1
arXiv PDF paper https://arxiv.org/pdf/2111.06119v1.pdf
Fine-grained image analysis (FGIA) ... targets analyzing visual objects from subordinate categories, e.g., species of birds or models of cars.
The small inter-class and large intra-class variation inherent to fine-grained image analysis makes it a challenging problem.
... in recent years we have witnessed remarkable progress in deep learning powered FGIA.
... present a systematic survey of these advances, where we attempt to re-define and broaden the field of FGIA by consolidating two fundamental fine-grained research areas -- fine-grained image recognition and fine-grained image retrieval.
... also review other key issues of FGIA, such as publicly available benchmark datasets and related domain-specific applications.
... conclude by highlighting several research directions and open problems which need further exploration from the community.
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