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Rethinking Multi-domain Generalization with A General Learning Objective, accepted by cvpr24

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Rethinking Multi-domain Generalization with A General Learning Objective, Accepted by CVPR24

Zhaorui Tan, Xi Yang, Kaizhu Huang

arxiv: https://arxiv.org/abs/2402.18853

This repo includes GMDG applied to classification, regression, and segmentation tasks.

Updated 2024/11/18 Hey there, I have a reported issue: "I noticed a mismatch between the reported results for the TerraInc dataset in the main text and the appendix. Specifically, in Table 7 of the main text, the mean accuracy of the proposed GMDG using ResNet-50 as the oracle model is 51.1%, while in Table 15 of the appendix, it is reported as 50.1%."

I am really sorry for the mismatch in the results. I have checked my raw results, and I need to clarify that the 51.1% in the main paper is correct. Here are the corrected results for each domain:

TerraIncognita

Seed Location 100 Location 38 Location 43 Location 46 Avg.
seed 0 58.58 50.24 55.79 43.53 52.04
seed 1 57.18 47.99 53.94 41.77 50.22
seed 2 67.05 43.52 55.76 37.82 51.04
mean 60.90 47.30 55.20 41.00 51.10

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