Unsupervised Data Augmentation or UDA is a semi-supervised learning method which achieves state-of-the-art results on a wide variety of language and vision ... ... <看更多>

2) Unsupervised Data Augmentation. 글의 첫 부분에도 언급을 했지만, 준지도학습 기반의 consistency training에서는 unlabeled 데이터에 대해 ... ... <看更多>

This repo contains a simple and clear PyTorch implementation of the main building blocks of "Unsupervised Data Augmentation for Consistency Training" by ... ... <看更多>

I am currently reading a paper: UNSUPERVISED DATA AUGMENTATION FOR CONSISTENCY TRAINING by Google and CMU last year. I think the method of ... ... <看更多>

Unsupervised Data Augmentation for Consistency training implemented in Pytorch ... Semi-supervised learning (SSL) one of the most promising paradigms to ... ... <看更多>

Unsupervised data augmentation (UDA):. Design data augmentation method for unlabeled data since unlabeled data is often larger. Consistency loss: Minimize ... ... <看更多>

Recently, it has been a key component of works like Noisy Student Training and Unsupervised Data Augmentation for Consistency Training. ... <看更多>

We present a framework for training GANs with explicit control over generated images. ... Unsupervised data augmentation for consistency training. ... <看更多>

Unsupervised learning of depth and ego-motion from video. sgml : 20191104 ... Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation 1. ... <看更多>

A survey on Image Data Augmentation for Deep Learning Generative ... problem of training data in deep learning image enhancement, an unsupervised network is ... ... <看更多>