HyperAI
HyperAI超神经
首页
算力平台
文档
资讯
论文
教程
数据集
百科
SOTA
LLM 模型天梯
GPU 天梯
顶会
开源项目
全站搜索
关于
中文
HyperAI
HyperAI超神经
Toggle sidebar
全站搜索…
⌘
K
全站搜索…
⌘
K
首页
SOTA
细粒度图像分类
Fine Grained Image Classification On Cub 200 1
Fine Grained Image Classification On Cub 200 1
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
Columns
模型名称
Accuracy
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
-
0 of 26 row(s) selected.
Previous
Next
Fine Grained Image Classification On Cub 200 1 | SOTA | HyperAI超神经