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Fine Grained Image Classification On Stanford 1

Metrics

Accuracy

Results

Performance results of various models on this benchmark

Paper Title
MP97.3%SR-GNN: Spatial Relation-aware Graph Neural Network for Fine-Grained Image Categorization
MPSA95.4%Multi-Granularity Part Sampling Attention for Fine-Grained Visual Classification
ViT-NeT (DeiT-III-B)93.6%ViT-NeT: Interpretable Vision Transformers with Neural Tree Decoder
µ2Net+ (ViT-L/16)93.5%A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems
SIM-OFE93.3%SIM-OFE: Structure Information Mining and Object-aware Feature Enhancement for Fine-Grained Visual Categorization
WS_DAN-SAC93.1%Fine-Grained Visual Classification using Self Assessment Classifier
SEB+EfficientNet-B593.0%On the Eigenvalues of Global Covariance Pooling for Fine-grained Visual Recognition
TPSKG92.5%Transformer with Peak Suppression and Knowledge Guidance for Fine-grained Image Recognition
RAMS-Trans92.4%RAMS-Trans: Recurrent Attention Multi-scale Transformer forFine-grained Image Recognition
TransFG92.3% (90.6%)TransFG: A Transformer Architecture for Fine-grained Recognition
IELT91.8%Fine-Grained Visual Classification via Internal Ensemble Learning Transformer
AFTrans91.6%A free lunch from ViT:Adaptive Attention Multi-scale Fusion Transformer for Fine-grained Visual Recognition
FFVT91.5%Feature Fusion Vision Transformer for Fine-Grained Visual Categorization
FAL-ViT91.1%An Attention-Locating Algorithm for Eliminating Background Effects in Fine-grained Visual Classification
MP-FGVC91.0%Delving into Multimodal Prompting for Fine-grained Visual Classification
API-Net90.3%Learning Attentive Pairwise Interaction for Fine-Grained Classification
ViT-B/16 (RPE w/ GAB)90.185%Understanding Gaussian Attention Bias of Vision Transformers Using Effective Receptive Fields
ImageNet + iNat on WS-DAN90%Domain Adaptive Transfer Learning on Visual Attention Aware Data Augmentation for Fine-grained Visual Categorization
SEF88.8%Learning Semantically Enhanced Feature for Fine-Grained Image Classification
DB87.7%Fine-grained Recognition: Accounting for Subtle Differences between Similar Classes
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Fine Grained Image Classification On Stanford 1 | SOTA | HyperAI