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Object Recognition 벤치마크

Object Recognition on shape bias

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shape bias

17.2 37.58 57.95 78.33 98.7 2018-11 2026-11 AlexNet — 42.9 (2018-11-29) GoogLeNet — 31.2 (2018-11-29) ResNet-50 — 22.1 (2018-11-29) VGG-16 — 17.2 (2018-11-29) SWSL (ResNeXt-101) — 49.8 (2019-05-02) SWSL (ResNet-50) — 28.6 (2019-05-02) ResNet-50 (with strong augmentations) — 62.2 (2019-11-20) SimCLR (ResNet-50x2) — 41.7 (2020-02-13) SimCLR (ResNet-50x4) — 40.7 (2020-02-13) SimCLR (ResNet-50x1) — 38.9 (2020-02-13) ResNet-50 (L2 eps 5.0 adv trained) — 69.5 (2020-07-16) CLIP (ViT-B) — 79.9 (2021-02-26) ViT-22B-384 — 86.4 (2023-02-10) ViT-22B-560 — 83.8 (2023-02-10) ViT-22B-224 — 78.0 (2023-02-10) Imagen — 98.7 (2023-09-28) Stable Diffusion — 92.7 (2023-09-28) Parti — 91.7 (2023-09-28) AlexNet — 42.9 (2018-11-29) SWSL (ResNeXt-101) — 49.8 (2019-05-02) ResNet-50 (with strong augmentations) — 62.2 (2019-11-20) ResNet-50 (L2 eps 5.0 adv trained) — 69.5 (2020-07-16) CLIP (ViT-B) — 79.9 (2021-02-26) ViT-22B-384 — 86.4 (2023-02-10) Imagen — 98.7 (2023-09-28)
RankModel shape bias PaperCodeYear
1 Imagen 98.7 Intriguing properties of generative classifiers SamsungSAILMontreal/ForestDiffusion 2023
2 Stable Diffusion 92.7 Intriguing properties of generative classifiers SamsungSAILMontreal/ForestDiffusion 2023
3 Parti 91.7 Intriguing properties of generative classifiers SamsungSAILMontreal/ForestDiffusion 2023
4 ViT-22B-384 86.4 Scaling Vision Transformers to 22 Billion Parameters lucidrains/flash-cosine-sim-attention 2023
5 ViT-22B-560 83.8 Scaling Vision Transformers to 22 Billion Parameters lucidrains/flash-cosine-sim-attention 2023
6 CLIP (ViT-B) 79.9 Learning Transferable Visual Models From Natural Language Supervision openai/CLIP · mlfoundations/open_clip · towhee-io/towhee · +79 2021
7 ViT-22B-224 78.0 Scaling Vision Transformers to 22 Billion Parameters lucidrains/flash-cosine-sim-attention 2023
8 ResNet-50 (L2 eps 5.0 adv trained) 69.5 Do Adversarially Robust ImageNet Models Transfer Better? MadryLab/robustness · lengstrom/gitlinks 2020
9 ResNet-50 (with strong augmentations) 62.2 The Origins and Prevalence of Texture Bias in Convolutional Neural Networks 2019
10 SWSL (ResNeXt-101) 49.8 Billion-scale semi-supervised learning for image classification facebookresearch/semi-supervised-ImageNet1K-models · leaderj1001/Billion-scale-semi-supervised-learning · salesforce/ensemble-of-averages · +1 2019
11 AlexNet 42.9 ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness rgeirhos/texture-vs-shape · rgeirhos/Stylized-ImageNet · LiYingwei/ShapeTextureDebiasedTraining · +4 2018
12 SimCLR (ResNet-50x2) 41.7 A Simple Framework for Contrastive Learning of Visual Representations tensorflow/models · google-research/simclr · lightly-ai/lightly · +93 2020
13 SimCLR (ResNet-50x4) 40.7 A Simple Framework for Contrastive Learning of Visual Representations tensorflow/models · google-research/simclr · lightly-ai/lightly · +93 2020
14 SimCLR (ResNet-50x1) 38.9 A Simple Framework for Contrastive Learning of Visual Representations tensorflow/models · google-research/simclr · lightly-ai/lightly · +93 2020
15 GoogLeNet 31.2 ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness rgeirhos/texture-vs-shape · rgeirhos/Stylized-ImageNet · LiYingwei/ShapeTextureDebiasedTraining · +4 2018
16 SWSL (ResNet-50) 28.6 Billion-scale semi-supervised learning for image classification facebookresearch/semi-supervised-ImageNet1K-models · leaderj1001/Billion-scale-semi-supervised-learning · salesforce/ensemble-of-averages · +1 2019
17 ResNet-50 22.1 ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness rgeirhos/texture-vs-shape · rgeirhos/Stylized-ImageNet · LiYingwei/ShapeTextureDebiasedTraining · +4 2018
18 VGG-16 17.2 ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness rgeirhos/texture-vs-shape · rgeirhos/Stylized-ImageNet · LiYingwei/ShapeTextureDebiasedTraining · +4 2018
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