Image Classification on ImageNet 1k (Top-1 Acc., Retention)
85.51Top-1 AccuracyConvNeXt-B
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| ConvNeXt-BModel=ConvNeXt-B, Method (Full vs VBP)=Full, MACs (G)=15.38, Parameters (M)=88.592025.07 | 85.51 | — | |
| ConvNeXt-SModel=ConvNeXt-S, Method (Full vs VBP)=Full, MACs (G)=8.71, Parameters (M)=50.222025.07 | 84.57 | — | |
| VBPModel=ConvNeXt-B, Method (Full vs VBP)=VBP, MACs (G)=8.91 (-42.1%), Parameters (M)=41.32 (-53.4%), Pruning Rate=50%, Evaluation Condition=VBP (Final)2025.07 | 83.4 | 97.6 | |
| ConvNeXt-TModel=ConvNeXt-T, Method (Full vs VBP)=Full, MACs (G)=4.47, Parameters (M)=28.592025.07 | 82.9 | — | |
| VBPModel=ConvNeXt-S, Method (Full vs VBP)=VBP, MACs (G)=5.11 (-41.3%), Parameters (M)=23.50 (-53.2%), Pruning Rate=50%, Evaluation Condition=VBP (Final)2025.07 | 82.82 | 97.9 | |
| VBPModel=ConvNeXt-T, Method (Full vs VBP)=VBP, MACs (G)=2.96 (-33.8%), Parameters (M)=12.61 (-55.9%), Pruning Rate=50%, Evaluation Condition=VBP (Final)2025.07 | 81.3 | 98.1 | |
| VBPModel=ConvNeXt-B, Method (Full vs VBP)=VBP, MACs (G)=8.91 (-42.1%), Parameters (M)=41.32 (-53.4%), Pruning Rate=50%, Evaluation Condition=Retention (Pre-finetuning)2025.07 | 57.1 | 66.8 | |
| VBPModel=ConvNeXt-S, Method (Full vs VBP)=VBP, MACs (G)=5.11 (-41.3%), Parameters (M)=23.50 (-53.2%), Pruning Rate=50%, Evaluation Condition=Retention (Pre-finetuning)2025.07 | 30.92 | 36.6 | |
| VBPModel=ConvNeXt-T, Method (Full vs VBP)=VBP, MACs (G)=2.96 (-33.8%), Parameters (M)=12.61 (-55.9%), Pruning Rate=50%, Evaluation Condition=Retention (Pre-finetuning)2025.07 | 16.8 | 20.3 |