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Image Classification on Food-101 (test)

96.879Top-1 Acc

Efficient Adaptive Ensembling

Updated 3d ago

Evaluation Results

Method
Efficient Adaptive Ensembling 2022.06	96.879	0.699	-	-	-	-
WiSE-FT 2021.09	96.2	-	-	-	-	-
SOTA 2022.06	96.18	-	-	-	-	-
SAM-final 2021.02	96.18	-	-	-	-	-
WiSE-FT 2021.09	96.1	-	-	-	-	-
SAM-baseline 2021.02	96.03	-	-	-	-	-
CLIP-ViT 2021.02	95.9	-	-	-	-	-
ALIGN 2021.02	95.88	-	-	-	-	-
Standard fine-tuning 2021.09	94.4	-	-	-	-	-
GPipe (AmoebaNet-B (18, 512)) 2018.11	93	-	-	-	-	-
CLIP-RN 2021.02	91.3	-	-	-	-	-
Full-tuning 2022.05	90.96	-	-	-	-	-
AdaptFormer-64 2022.05	90.89	-	-	-	-	-
Method [30] 2018.11	90.4	-	-	-	-	-
VPT 2022.05	90.16	-	-	-	-	-
AttentiveNAS-A6 2020.11	89.6	-	-	-	-	-
CLIP-RN 2021.02	88.9	-	-	-	-	-
EfficientNet-B1 2020.11	88.9	-	-	-	-	-
CLIP-ViT 2021.02	88.8	-	-	-	-	-
ReXNet (x1.0) 2020.07	88.4	-	-	-	-	-
Linear 2022.05	88.14	-	-	-	-	-
AttentiveNAS-A1 2020.11	88.1	-	-	-	-	-
EfficientNet-B0 2020.11	87.6	-	-	-	-	-
SOMNet 2019.06	87.5	-	-	-	-	-
EfficientNet-B0 2020.07	87.5	-	-	-	-	-
ResNet50 2020.07	87	-	-	-	-	-
CLIP-RN 2021.02	86.4	-	-	-	-	-
Supervised 2021.12	84.6	-	-	-	-	-
CurriculumNet 2019.06	84.5	-	-	-	-	-
TransBoost 2022.05	84.3	4.42	-	-	-	-
PENCIL 2019.06	83.1	-	-	-	-	-
Zhuang et al. 2019.06	82.5	-	-	-	-	-
MLNT 2019.06	82.5	-	-	-	-	-
MANO-tiny 2025.07	82.48	-	-	-	-	-
ProDA 2022.05	82.4	-	-	-	-	-
MMCL 2021.12	82.39	-	-	-	-	-
CLIP-Refine 2025.04	81.87	-	-	-	-	-
ProDA 2022.05	81.7	-	-	-	-	-
Tanaka et al. 2019.06	81.5	-	-	-	-	-
LM RN50 2021.02	81.3	-	-	-	-	-
DRAE 2019.06	81.1	-	-	-	-	-
SL 2019.06	80.9	-	-	-	-	-
Sukhbaatar et al. 2019.06	80.8	-	-	-	-	-
ProDA 2022.05	80.8	-	-	-	-	-
ProDA 2022.05	80.8	-	-	-	-	-
Zero-Shot CLIP 2022.05	80.6	-	-	-	-	-
ProDA 2022.05	80.6	-	-	-	-	-
PCL-v2 2021.12	80.34	-	-	-	-	-
ViT-base 2025.07	80.31	-	-	-	-	-
Pre-trained 2025.04	80.21	-	-	-	-	-
HyCD 2025.04	80.19	-	-	-	-	-
Self-KD 2025.04	80.02	-	-	-	-	-
Standard Inductive 2022.05	79.88	-	-	-	-	-
CoOp 2022.05	79.3	-	-	-	-	-
AD-MIL 2019.06	79.2	-	-	-	-	-
MOCHI 2021.12	78.9	-	-	-	-	-
PCL-v1 2021.12	78.3	-	-	-	-	-
BAM 2024.08	78.2	-	-	-	-	-
CoOp 2022.05	77.8	-	-	-	-	-
SCE 2022.12	77.7	-	-	-	-	-
Ours 2022.04	77.5	-	-	-	-	-
CoOp 2022.05	77.5	-	-	-	-	-
ResNet50 2019.06	77.4	-	-	-	-	-
MoCo 2021.12	77.28	-	-	-	-	-
MoCo-v2 2021.12	77.19	-	-	-	-	-
CoOp 2022.05	77	-	-	-	-	-
SwinV2-T 2025.07	76.96	-	-	-	-	-
InsDis 2021.12	76.78	-	-	-	-	-
NNCLR 2022.12	76.7	-	-	-	-	-
NNCLR 2024.08	76.7	-	-	-	-	-
CoOp 2022.05	76.4	-	-	-	-	-
BYOL 2022.12	75.3	-	-	-	-	-
BYOL 2024.08	75.3	-	-	-	-	-
Linear Probe CLIP 2022.05	73.7	-	-	-	-	-
HyCD + Lalign 2025.04	73.31	-	-	-	-	-
SimCLR 2022.12	72.8	-	-	-	-	-
Supervised 2022.12	72.3	-	-	-	-	-
DeiT-small 2025.07	71.39	-	-	-	-	-
m²-mix 2025.04	71.27	-	-	-	-	-
Contrastive 2025.04	70.31	-	-	-	-	-
SimCLR 2024.08	68.4	-	-	-	-	-
Linear Probe CLIP 2022.05	67.1	-	-	-	-	-
Image only 2022.04	65.9	-	-	-	-	-
Linear Probe CLIP 2022.05	56.8	-	-	-	-	-
Linear Probe CLIP 2022.05	45.1	-	-	-	-	-
New baseline 2022.04	44.3	-	-	-	-	-
Linear Probe CLIP 2022.05	31.4	-	-	-	-	-
CyCLIP 2022.05	14	-	-	-	-	-
CLIP 2022.05	13.3	-	-	-	-	-
Baseline 2018.08	-	-	18.3	-	-	-
Our Baseline 2018.08	-	-	15	-	-	-
CurriculumNet 2018.08	-	-	12.7	-	-	-
Finetune 2022.08	-	-	-	60.9	-	-
Finetune 2022.08	-	-	-	84.5	-	-
Finetune 2022.08	-	-	-	93.1	-	-
Semi-ViT 2022.08	-	-	-	82.1	-	-
Semi-ViT 2022.08	-	-	-	91.3	-	-
Supervised-IN 2022.01	-	-	-	72.3	-	-
SimCLR 2022.01	-	-	-	68.4	-	-
BYOL 2022.01	-	-	-	75.3	-	-

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