16 citations · 27 across the 6 of their papers we have counts for
6 papers
AllRestorer: All-in-One Transformer for Image Restoration under Composite Degradations
Jiawei Mao, Yu Yang, Xuesong Yin +2
Image restoration models often face the simultaneous interaction of multiple degradations in real-world scenarios. Existing approaches typically handle single or composite degradat…
SwinStyleformer is a favorable choice for image inversion
Jiawei Mao, Guangyi Zhao, Xuesong Yin +1
This paper proposes the first pure Transformer structure inversion network called SwinStyleformer, which can compensate for the shortcomings of the CNNs inversion framework by hand…
Medical supervised masked autoencoders: Crafting a better masking strategy and efficient fine-tuning schedule for medical image classification
Jiawei Mao, Shujian Guo, Yuanqi Chang +2
Masked autoencoders (MAEs) have displayed significant potential in the classification and semantic segmentation of medical images in the last year. Due to the high similarity of hu…
Star-Net: Improving Single Image Desnowing Model With More Efficient Connection and Diverse Feature Interaction
Jiawei Mao, Yuanqi Chang, Xuesong Yin +1
Compared to other severe weather image restoration tasks, single image desnowing is a more challenging task. This is mainly due to the diversity and irregularity of snow shape, whi…
POSTER++: A simpler and stronger facial expression recognition network
Jiawei Mao, Rui Xu, Xuesong Yin +3
Facial expression recognition (FER) plays an important role in a variety of real-world applications such as human-computer interaction. POSTER achieves the state-of-the-art (SOTA)…
Masked autoencoders are effective solution to transformer data-hungry
Jiawei Mao, Honggu Zhou, Xuesong Yin +1
Vision Transformers (ViTs) outperforms convolutional neural networks (CNNs) in several vision tasks with its global modeling capabilities. However, ViT lacks the inductive bias inh…