Fine Grained Image Classification On Cub 200 1

Metrics

Accuracy

Results

Performance results of various models on this benchmark

		Paper Title	Repository
HERBS	93.1%	Fine-grained Visual Classification with High-temperature Refinement and Background Suppression
PIM	92.8	A Novel Plug-in Module for Fine-Grained Visual Classification
CAP	91.8	Context-aware Attentional Pooling (CAP) for Fine-grained Visual Classification
SWAG (ViT H/14)	91.7	Revisiting Weakly Supervised Pre-Training of Visual Perception Models
TransFG	91.7	TransFG: A Transformer Architecture for Fine-grained Recognition
FFVT	91.6	Feature Fusion Vision Transformer for Fine-Grained Visual Categorization
DATL	91.2	Domain Adaptive Transfer Learning on Visual Attention Aware Data Augmentation for Fine-grained Visual Categorization	-
CAL	90.6	Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
HOI-Net	90.02%	High-Order-Interaction for weakly supervised Fine-Grained Visual Categorization	-
TBMSL-Net	89.6	Multi-branch and Multi-scale Attention Learning for Fine-Grained Visual Categorization
FBSD	89.5	Feature Boosting, Suppression, and Diversification for Fine-Grained Visual Classification
WS-DAN	89.4	See Better Before Looking Closer: Weakly Supervised Data Augmentation Network for Fine-Grained Visual Classification
ELP	88.8	A Simple Episodic Linear Probe Improves Visual Recognition in the Wild	-
MPN-COV	88.7	Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization
FixSENet-154	88.7	Fixing the train-test resolution discrepancy
ResNet-50	88.59	PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and Humans
DenseNet161+MM+FRL	88.5	Learning Class Unique Features in Fine-Grained Visual Classification	-
LIO	88.0	Look-into-Object: Self-supervised Structure Modeling for Object Recognition
TASN	87.9	Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-grained Image Recognition
Nts-Net	87.5	Are These Birds Similar: Learning Branched Networks for Fine-grained Representations	-

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Fine Grained Image Classification On Cub 200 1

Metrics

Results