Fine Grained Image Classification On Nabirds

评估指标

Accuracy

评测结果

各个模型在此基准测试上的表现结果

		Paper Title	Repository
HERBS	93.0%	Fine-grained Visual Classification with High-temperature Refinement and Background Suppression
MetaFormer (MetaFormer-2,384)	93.0%	MetaFormer: A Unified Meta Framework for Fine-Grained Recognition
PIM	92.8%	A Novel Plug-in Module for Fine-Grained Visual Classification
MPSA	92.5%	Multi-Granularity Part Sampling Attention for Fine-Grained Visual Classification	-
CSQA-Net	92.3%	Context-Semantic Quality Awareness Network for Fine-Grained Visual Categorization	-
I2-HOFI	92.12%	Interweaving Insights: High-Order Feature Interaction for Fine-Grained Visual Recognition	-
CGL	91.7%	Universal Fine-grained Visual Categorization by Concept Guided Learning	-
SR-GNN	91.2%	SR-GNN: Spatial Relation-aware Graph Neural Network for Fine-Grained Image Categorization
FAL-ViT	91.1%	An Attention-Locating Algorithm for Eliminating Background Effects in Fine-grained Visual Classification	-
MP-FGVC	91.0%	Delving into Multimodal Prompting for Fine-grained Visual Classification	-
CAP	91.0%	Context-aware Attentional Pooling (CAP) for Fine-grained Visual Classification
TransIFC	90.9%	TransIFC: Invariant Cues-aware Feature Concentration Learning for Efficient Fine-grained Bird Image Classification	-
TransFG	90.8%	TransFG: A Transformer Architecture for Fine-grained Recognition
IELT	90.8%	Fine-Grained Visual Classification via Internal Ensemble Learning Transformer	-
FVE	90.3%	End-to-end Learning of a Fisher Vector Encoding for Part Features in Fine-grained Recognition
TPSKG	90.1%	Transformer with Peak Suppression and Knowledge Guidance for Fine-grained Image Recognition	-
FixSENet-154	89.2%	Fixing the train-test resolution discrepancy
MGE-CNN	88.6%	Learning a Mixture of Granularity-Specific Experts for Fine-Grained Categorization	-
CS-Part	88.5%	Classification-Specific Parts for Improving Fine-Grained Visual Categorization
CS-Parts	88.5%	Classification-Specific Parts for Improving Fine-Grained Visual Categorization

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