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SOTA
Fine-Grained Image Classification
Fine Grained Image Classification On Fgvc
Fine Grained Image Classification On Fgvc
Metrics
Accuracy
FLOPS
PARAMS
Results
Performance results of various models on this benchmark
Columns
Model Name
Accuracy
FLOPS
PARAMS
Paper Title
I2-HOFI
96.42%
-
-
Interweaving Insights: High-Order Feature Interaction for Fine-Grained Visual Recognition
SR-GNN
95.4
9.8
30.9
SR-GNN: Spatial Relation-aware Graph Neural Network for Fine-Grained Image Categorization
Inceptionv4
95.11
-
-
Non-binary deep transfer learning for image classification
CAP
94.9%
-
34.2
Context-aware Attentional Pooling (CAP) for Fine-grained Visual Classification
CSQA-Net
94.7%
-
-
Context-Semantic Quality Awareness Network for Fine-Grained Visual Categorization
CMAL-Net
94.7%
-
-
Learn from Each Other to Classify Better: Cross-layer Mutual Attention Learning for Fine-grained Visual Classification
TBMSL-Net
94.7%
-
-
Multi-branch and Multi-scale Attention Learning for Fine-Grained Visual Categorization
PART
94.6%
-
-
Part-guided Relational Transformers for Fine-grained Visual Recognition
AENet
94.5%
-
-
Alignment Enhancement Network for Fine-grained Visual Categorization
SaSPA + CAL
94.5
-
-
Advancing Fine-Grained Classification by Structure and Subject Preserving Augmentation
CAL
94.2
-
-
Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
CGL
94.2%
-
-
Universal Fine-grained Visual Categorization by Concept Guided Learning
AttNet & AffNet
94.1%
-
-
Fine-Grained Visual Classification with Efficient End-to-end Localization
CCFR
94.1%
-
-
Re-rank Coarse Classification with Local Region Enhanced Features for Fine-Grained Image Recognition
DenseNet161+MM+FRL
94.0 %
-
-
Learning Class Unique Features in Fine-Grained Visual Classification
API-Net
93.9%
-
-
Learning Attentive Pairwise Interaction for Fine-Grained Classification
CMN
93.8%
-
-
-
DF-GMM
93.8%
-
-
Weakly Supervised Fine-Grained Image Classification via Guassian Mixture Model Oriented Discriminative Learning
Multi Granularity
93.6%
-
-
Your "Flamingo" is My "Bird": Fine-Grained, or Not
BCN
93.5%
-
-
Fine-Grained Visual Classification with Batch Confusion Norm
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