Efficient Training of Visual Transformers with Small Datasets

Last update: Dec 25, 2022

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Overview

Efficient Training of Visual Transformers with Small Datasets

To appear in NerIPS 2021.

[arXiv][code]
Yahui Liu^1,3, Enver Sangineto¹, Wei Bi², Nicu Sebe¹, Bruno Lepri³, Marco De Nadai³
¹University of Trento, Italy, ²Tencent AI Lab, China, ³Bruno Kessler Foundation, Italy.

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Owner

Yahui Liu

Yahui Liu currently studies in Multimedia and Human Understanding Group (MHUG), University of Trento, Italy.

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Efficient Training of Visual Transformers with Small Datasets

Related tags

Overview

Efficient Training of Visual Transformers with Small Datasets

Owner

Yahui Liu

Code for the paper "MASTER: Multi-Aspect Non-local Network for Scene Text Recognition" (Pattern Recognition 2021)

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[AI6122] Text Data Management & Processing

Code of Periodic Activation Functions Induce Stationarity

Light-Head R-CNN

Source code for the ACL-IJCNLP 2021 paper entitled "T-DNA: Taming Pre-trained Language Models with N-gram Representations for Low-Resource Domain Adaptation" by Shizhe Diao et al.

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