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Fine Grained Image Classification On Stanford
Fine Grained Image Classification On Stanford
Metriken
Accuracy
PARAMS
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
Accuracy
PARAMS
Paper Title
Repository
DeiT-B
93.3%
86M
Training data-efficient image transformers & distillation through attention
-
SEB+EfficientNet-B5
94.6%
-
On the Eigenvalues of Global Covariance Pooling for Fine-grained Visual Recognition
S3N
94.7%
-
Selective Sparse Sampling for Fine-Grained Image Recognition
PMG
95.1%
-
Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches
PCA
94.6%
-
Progressive Co-Attention Network for Fine-grained Visual Classification
SaSPA + CAL
95.72
-
Advancing Fine-Grained Classification by Structure and Subject Preserving Augmentation
ViT-L (attn finetune)
93.8%
-
Three things everyone should know about Vision Transformers
AENet
94.0%
-
Alignment Enhancement Network for Fine-grained Visual Categorization
-
ResMLP-12
84.6%
-
ResMLP: Feedforward networks for image classification with data-efficient training
SR-GNN
96.1
30.9
SR-GNN: Spatial Relation-aware Graph Neural Network for Fine-Grained Image Categorization
RDNet-T (224 res, IN-1K pretrained)
93.9%
24M
DenseNets Reloaded: Paradigm Shift Beyond ResNets and ViTs
ResNet50 (A1)
92.7%
24M
ResNet strikes back: An improved training procedure in timm
Inceptionv4
95.35%
-
Non-binary deep transfer learning for image classification
WS-DAN
94.5%
-
See Better Before Looking Closer: Weakly Supervised Data Augmentation Network for Fine-Grained Visual Classification
CCFR
95.5%
-
Re-rank Coarse Classification with Local Region Enhanced Features for Fine-Grained Image Recognition
-
MPSA
95.4%
-
Multi-Granularity Part Sampling Attention for Fine-Grained Visual Classification
CIN
94.5%
-
Channel Interaction Networks for Fine-Grained Image Categorization
-
DF-GMM
94.8%
-
Weakly Supervised Fine-Grained Image Classification via Guassian Mixture Model Oriented Discriminative Learning
-
MPFG + CLIP
86.79
-
Multiscale patch-based feature graphs for image classification
TransFG
94.8%
-
TransFG: A Transformer Architecture for Fine-grained Recognition
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