| SR-GNN: Spatial Relation-aware Graph Neural Network for Fine-Grained Image Categorization | ✓ Link | 97.3% | MP | 2022-09-05 |
| Multi-Granularity Part Sampling Attention for Fine-Grained Visual Classification | ✓ Link | 95.4% | MPSA | 2024-08-16 |
| ViT-NeT: Interpretable Vision Transformers with Neural Tree Decoder | ✓ Link | 93.6% | ViT-NeT (DeiT-III-B) | 2022-07-17 |
| A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems | ✓ Link | 93.5% | µ2Net+ (ViT-L/16) | 2022-09-15 |
| SIM-OFE: Structure Information Mining and Object-aware Feature Enhancement for Fine-Grained Visual Categorization | | 93.3% | SIM-OFE | 2024-09-18 |
| Fine-Grained Visual Classification using Self Assessment Classifier | ✓ Link | 93.1% | WS_DAN-SAC | 2022-05-21 |
| On the Eigenvalues of Global Covariance Pooling for Fine-grained Visual Recognition | ✓ Link | 93.0% | SEB+EfficientNet-B5 | 2022-05-26 |
| Transformer with Peak Suppression and Knowledge Guidance for Fine-grained Image Recognition | | 92.5% | TPSKG | 2021-07-14 |
| RAMS-Trans: Recurrent Attention Multi-scale Transformer forFine-grained Image Recognition | | 92.4% | RAMS-Trans | 2021-07-17 |
| Structural feature enhanced transformer for fine-grained image recognition | | 92.4 | SFETrans | 2025-06-14 |
| TransFG: A Transformer Architecture for Fine-grained Recognition | ✓ Link | 92.3% (90.6%) | TransFG | 2021-03-14 |
| Fine-Grained Visual Classification via Internal Ensemble Learning Transformer | ✓ Link | 91.8% | IELT | 2023-02-13 |
| A free lunch from ViT:Adaptive Attention Multi-scale Fusion Transformer for Fine-grained Visual Recognition | | 91.6% | AFTrans | 2021-10-04 |
| Feature Fusion Vision Transformer for Fine-Grained Visual Categorization | ✓ Link | 91.5% | FFVT | 2021-07-06 |
| An Attention-Locating Algorithm for Eliminating Background Effects in Fine-grained Visual Classification | ✓ Link | 91.1% | FAL-ViT | 2025-01-28 |
| Delving into Multimodal Prompting for Fine-grained Visual Classification | | 91.0% | MP-FGVC | 2023-09-16 |
| Learning Attentive Pairwise Interaction for Fine-Grained Classification | ✓ Link | 90.3% | API-Net | 2020-02-24 |
| Understanding Gaussian Attention Bias of Vision Transformers Using Effective Receptive Fields | ✓ Link | 90.185% | ViT-B/16 (RPE w/ GAB) | 2023-05-08 |
| Domain Adaptive Transfer Learning on Visual Attention Aware Data Augmentation for Fine-grained Visual Categorization | | 90% | ImageNet + iNat on WS-DAN | 2020-10-06 |
| Learning Semantically Enhanced Feature for Fine-Grained Image Classification | ✓ Link | 88.8% | SEF | 2020-06-24 |
| Fine-grained Recognition: Accounting for Subtle Differences between Similar Classes | | 87.7% | DB | 2019-12-14 |
| PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and Humans | ✓ Link | 86.31% | ResNet-50 | 2023-08-25 |
| Pairwise Confusion for Fine-Grained Visual Classification | ✓ Link | 83.75% | PC-DenseNet-161 | 2017-05-22 |
| Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets | ✓ Link | 61.2% | EfficientNet-B0 (BSConv-S) | 2020-03-30 |