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SOTA
Image Classification
Image Classification On Places205
Image Classification On Places205
Metrics
Top 1 Accuracy
Results
Performance results of various models on this benchmark
Columns
Model Name
Top 1 Accuracy
Paper Title
Repository
MixMIM-L
69.3
MixMAE: Mixed and Masked Autoencoder for Efficient Pretraining of Hierarchical Vision Transformers
-
SEER
66.0
Self-supervised Pretraining of Visual Features in the Wild
-
AutoMix (ResNet-50 Supervised)
64.1
AutoMix: Unveiling the Power of Mixup for Stronger Classifiers
-
MAE (ViT-H, 448)
66.8
Masked Autoencoders Are Scalable Vision Learners
-
InternImage-H
71.7%
InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions
-
SwAV
56.7%
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
-
SAMix (ResNet-50 Supervised)
64.3
Boosting Discriminative Visual Representation Learning with Scenario-Agnostic Mixup
-
MixMIM-B
68.3
MixMAE: Mixed and Masked Autoencoder for Efficient Pretraining of Hierarchical Vision Transformers
-
ResNet-50 (Supervised)
53.2%
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
-
Barlow Twins (ResNet-50)
54.1%
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
-
MoCo v2
52.9
Improved Baselines with Momentum Contrastive Learning
-
SEER (RegNet10B - finetuned - 384px)
69.0
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
-
BYOL
54.0
Bootstrap your own latent: A new approach to self-supervised Learning
-
RegNetY-128GF (Supervised)
62.7
Self-supervised Pretraining of Visual Features in the Wild
-
SimCLR
53.3
A Simple Framework for Contrastive Learning of Visual Representations
-
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