activity
20162021
most citedImage Augmentations for GAN Training

116 citations · 263 across the 8 of their papers we have counts for

collaborators

21 papers

cs.CV2021

Learning from Weakly-labeled Web Videos via Exploring Sub-Concepts

Kunpeng Li, Zizhao Zhang, Guanhang Wu +5

Learning visual knowledge from massive weakly-labeled web videos has attracted growing research interests thanks to the large corpus of easily accessible video data on the Internet…

cs.CV2020

PseudoSeg: Designing Pseudo Labels for Semantic Segmentation

Yuliang Zou, Zizhao Zhang, Han Zhang +4

Recent advances in semi-supervised learning (SSL) demonstrate that a combination of consistency regularization and pseudo-labeling can effectively improve image classification accu…

cs.LG2020116 cited

Image Augmentations for GAN Training

Zhengli Zhao, Zizhao Zhang, Ting Chen +2

Data augmentations have been widely studied to improve the accuracy and robustness of classifiers. However, the potential of image augmentation in improving GAN models for image sy…

cs.CV2020

A Simple Semi-Supervised Learning Framework for Object Detection

Kihyuk Sohn, Zizhao Zhang, Chun-Liang Li +3

Semi-supervised learning (SSL) has a potential to improve the predictive performance of machine learning models using unlabeled data. Although there has been remarkable recent prog…

physics.app-ph2020

Electrical probing of COVID-19 spike protein receptor binding domain via a graphene field-effect transistor

Xiaoyan Zhang, Qige Qi, Qiushi Jing +9

Here, in an effort towards facile and fast screening/diagnosis of novel coronavirus disease 2019 (COVID-19), we combined the unprecedently sensitive graphene field-effect transisto…

stat.ML2020

Improved Consistency Regularization for GANs

Zhengli Zhao, Sameer Singh, Honglak Lee +3

Recent work has increased the performance of Generative Adversarial Networks (GANs) by enforcing a consistency cost on the discriminator. We improve on this technique in several wa…