Web: http://arxiv.org/abs/2206.07565

June 16, 2022, 1:11 a.m. | Benjamin Feuer, Ameya Joshi, Chinmay Hegde

cs.LG updates on arXiv.org arxiv.org

State-of-the-art image classifiers trained on massive datasets (such as
ImageNet) have been shown to be vulnerable to a range of both intentional and
incidental distribution shifts. On the other hand, several recent classifiers
with favorable out-of-distribution (OOD) robustness properties have emerged,
achieving high accuracy on their target tasks while maintaining their
in-distribution accuracy on challenging benchmarks. We present a meta-analysis
on a wide range of publicly released models, most of which have been published
over the last twelve months. Through …

analysis arxiv cv meta meta-analysis models

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