Основные понятия
Proposing a Context-Semantic Quality Awareness Network (CSQA-Net) for Fine-Grained Visual Categorization to enhance feature representations and quality evaluation.
Аннотация
The article introduces the CSQA-Net, focusing on improving fine-grained visual categorization by addressing the quality of extracted visual representations. The network includes modules like MPMSCA and MLSQE to capture discriminative features and evaluate semantic quality progressively. Experiments show superior performance on popular FGVC datasets.
Статистика
Comprehensive experiments demonstrate the superiority of CSQA-Net in comparison with state-of-the-art methods.
Цитаты
"We propose an end-to-end Context-Semantic Quality Awareness Network (CSQA-Net), which explores more detailed part descriptors to regularize global semantics."
"Benefiting from the proposed MPMSCA and the MLSQE modules, our CSQA-Net can discover and recover subtle yet distinctive clues buried in object representation."