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SOTA
Fine-Grained Image Classification
Fine Grained Image Classification On Cub 200
Fine Grained Image Classification On Cub 200
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Columns
Model Name
Accuracy
Paper Title
MetaFormer (MetaFormer-2,384)
92.9%
MetaFormer: A Unified Meta Framework for Fine-Grained Recognition
MPSA
92.8%
Multi-Granularity Part Sampling Attention for Fine-Grained Visual Classification
PIM
92.8%
A Novel Plug-in Module for Fine-Grained Visual Classification
CGL
92.6%
Universal Fine-grained Visual Categorization by Concept Guided Learning
CSQA-Net
92.6%
Context-Semantic Quality Awareness Network for Fine-Grained Visual Categorization
SIM-OFE
92.3%
SIM-OFE: Structure Information Mining and Object-aware Feature Enhancement for Fine-Grained Visual Categorization
Inception-v3
92.3%
The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition
DCAL
92.0%
Dual Cross-Attention Learning for Fine-Grained Visual Categorization and Object Re-Identification
SR-GNN
91.9%
SR-GNN: Spatial Relation-aware Graph Neural Network for Fine-Grained Image Categorization
MP-FGVC
91.8%
Delving into Multimodal Prompting for Fine-grained Visual Classification
CAP
91.8%
Context-aware Attentional Pooling (CAP) for Fine-grained Visual Classification
SIM-Trans
91.8%
SIM-Trans: Structure Information Modeling Transformer for Fine-grained Visual Categorization
MP-MGVC
91.8%
Delving into Multimodal Prompting for Fine-grained Visual Classification
IELT
91.8%
Fine-Grained Visual Classification via Internal Ensemble Learning Transformer
ViT-SAC
91.8%
Fine-Grained Visual Classification using Self Assessment Classifier
TransFG
91.7%
TransFG: A Transformer Architecture for Fine-grained Recognition
FAL-ViT
91.7%
An Attention-Locating Algorithm for Eliminating Background Effects in Fine-grained Visual Classification
ViT-NeT (SwinV2-B)
91.7%
ViT-NeT: Interpretable Vision Transformers with Neural Tree Decoder
FFVT
91.6%
Feature Fusion Vision Transformer for Fine-Grained Visual Categorization
I2-HOFI
91.6%
Interweaving Insights: High-Order Feature Interaction for Fine-Grained Visual Recognition
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Fine Grained Image Classification On Cub 200 | SOTA | HyperAI