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[arxiv-cs. CV] 汇总-2025. 11. 26-计算机视觉论文 - 知乎 A Training-Free Approach for Multi-ID Customization via Attention Adjustment and Spatial Control 中文翻译：一种通过注意力调整和空间控制实现多ID定制的免训练方法
Multi-scale local regional attention fusion using visual transformers . . . Many researchers have tackled the challenges of fine-grained image classification by integrating traditional CNN backbones with attention mechanisms, thereby improving the model’s capacity to capture key features and boost classification accuracy
Awesome Fine-Grained Image Classification - GitHub Multi objective classification with cascaded FC classifiers for each hierarchy level + loss to bring same fine-grained class together and same coarse class closer than different coarse
Rethinking Attention Mechanism: Channel Re-attention and Spatial Multi . . . Our method does not require bounding boxes part annotations and can be trained in an end-to-end way Extensive experimental results on several fine-grained benchmark datasets demonstrate that our approach achieves state-of-the-art performance