V0.2.5-Mixup-Place205-Weights

A collection of weights and logs for mixup classification benchmark on Place205 (download, config). You can download all files from Baidu Cloud (4m94).

• All compared methods adopt ResNet-18/50 architectures and are trained 100 epochs using the PyTorch training recipe. The training and testing image size is 224 with the CenterCrop ratio of 0.85. We search $\alpha$ in $Beta(\alpha, \alpha)$ for all compared methods.
• The median of top-1 accuracy in the last 5 training epochs is reported for ResNet variants.
• Visualization of mixed samples from AutoMix and SAMix are provided in zip files. [2022-08-22] Update MixBlock keys in AutoMix and SAMix checkpoints.
• Test pre-trained weights with tools/dist_test.sh or fine-tune pre-trained models tools/dist_train.sh with --load_checkpoint.

Mixup Classification Benchmark on Place205

Backbones	ResNet-18 top-1	ResNet-50 top-1
Vanilla	59.63	63.10
MixUp [ICLR'2018]	59.33	63.01
CutMix [ICCV'2019]	59.21	63.75
ManifoldMix [ICML'2019]	59.46	63.23
SaliencyMix [ICLR'2021]	59.50	63.33
FMix [Arixv'2020]	59.51	63.63
PuzzleMix [ICML'2020]	59.62	63.91
ResizeMix [Arixv'2020]	59.66	63.88
AutoMix [ECCV'2022]	59.74	64.06
SAMix [Arxiv'2021]	59.86	64.27