Search Results for author: Aoming Liu

Found 2 papers, 1 papers with code

Direct Differentiable Augmentation Search

1 code implementation ICCV 2021 Aoming Liu, Zehao Huang, Zhiwu Huang, Naiyan Wang

Data augmentation has been an indispensable tool to improve the performance of deep neural networks, however the augmentation can hardly transfer among different tasks and datasets.

AutoML Data Augmentation +4

Neural Architecture Search as Sparse Supernet

no code implementations31 Jul 2020 Yan Wu, Aoming Liu, Zhiwu Huang, Siwei Zhang, Luc van Gool

This paper aims at enlarging the problem of Neural Architecture Search (NAS) from Single-Path and Multi-Path Search to automated Mixed-Path Search.

Neural Architecture Search

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