Fine-grained recognition with learnable semantic data augmentation
Fine-grained image recognition is a longstanding computer vision challenge that focuses on
differentiating objects belonging to multiple subordinate categories within the same meta …
differentiating objects belonging to multiple subordinate categories within the same meta …
Discrimination-aware mechanism for fine-grained representation learning
Recently, with the emergence of retrieval requirements for certain individual in the same
superclass, eg, birds, persons, cars, fine-grained recognition task has attracted a significant …
superclass, eg, birds, persons, cars, fine-grained recognition task has attracted a significant …
Look closer to see better: Recurrent attention convolutional neural network for fine-grained image recognition
Recognizing fine-grained categories (eg, bird species) is difficult due to the challenges of
discriminative region localization and fine-grained feature learning. Existing approaches …
discriminative region localization and fine-grained feature learning. Existing approaches …
Re-rank coarse classification with local region enhanced features for fine-grained image recognition
Fine-grained image recognition is very challenging due to the difficulty of capturing both
semantic global features and discriminative local features. Meanwhile, these two features …
semantic global features and discriminative local features. Meanwhile, these two features …
Stochastic partial swap: Enhanced model generalization and interpretability for fine-grained recognition
Learning mid-level representation for fine-grained recognition is easily dominated by a
limited number of highly discriminative patterns, degrading its robustness and generalization …
limited number of highly discriminative patterns, degrading its robustness and generalization …
Learning rich part hierarchies with progressive attention networks for fine-grained image recognition
We investigate the localization of subtle yet discriminative parts for fine-grained image
recognition. Based on the observation that such parts typically exist within a hierarchical …
recognition. Based on the observation that such parts typically exist within a hierarchical …
Looking for the devil in the details: Learning trilinear attention sampling network for fine-grained image recognition
Learning subtle yet discriminative features (eg, beak and eyes for a bird) plays a significant
role in fine-grained image recognition. Existing attention-based approaches localize and …
role in fine-grained image recognition. Existing attention-based approaches localize and …
A collaborative gated attention network for fine-grained visual classification
Q Zhu, W Kuang, Z Li - Displays, 2023 - Elsevier
Fine-grained image classification aims at subdividing large coarse-grained categories into
finer-grained subcategories. Most existing fine-grained research methods use a single …
finer-grained subcategories. Most existing fine-grained research methods use a single …
Object-part attention model for fine-grained image classification
Fine-grained image classification is to recognize hundreds of subcategories belonging to
the same basic-level category, such as 200 subcategories belonging to the bird, which is …
the same basic-level category, such as 200 subcategories belonging to the bird, which is …
Intra-class part swapping for fine-grained image classification
Recent works such as Mixup and Cutmix have demonstrated the effectiveness of
augmenting training data for deep models. These methods generate new data by generally …
augmenting training data for deep models. These methods generate new data by generally …