4 citations · 14 across the 8 of their papers we have counts for
8 papers
LLaMA-Reg: Using LLaMA 2 for Unsupervised Medical Image Registration
Mingrui Ma, Yu Yang
Medical image registration is an essential topic in medical image analysis. In this paper, we propose a method for medical image registration using a pretrained large language mode…
Learning to Annotate Part Segmentation with Gradient Matching
Yu Yang, Xiaotian Cheng, Hakan Bilen +1
The success of state-of-the-art deep neural networks heavily relies on the presence of large-scale labelled datasets, which are extremely expensive and time-consuming to annotate.…
Distilling Representations from GAN Generator via Squeeze and Span
Yu Yang, Xiaotian Cheng, Chang Liu +2
In recent years, generative adversarial networks (GANs) have been an actively studied topic and shown to successfully produce high-quality realistic images in various domains. The…
Local Manifold Augmentation for Multiview Semantic Consistency
Yu Yang, Wing Yin Cheung, Chang Liu +1
Multiview self-supervised representation learning roots in exploring semantic consistency across data of complex intra-class variation. Such variation is not directly accessible an…
ILSGAN: Independent Layer Synthesis for Unsupervised Foreground-Background Segmentation
Qiran Zou, Yu Yang, Wing Yin Cheung +2
Unsupervised foreground-background segmentation aims at extracting salient objects from cluttered backgrounds, where Generative Adversarial Network (GAN) approaches, especially lay…
Which Style Makes Me Attractive? Interpretable Control Discovery and Counterfactual Explanation on StyleGAN
Bo Li, Qiulin Wang, Jiquan Pei +2
The semantically disentangled latent subspace in GAN provides rich interpretable controls in image generation. This paper includes two contributions on semantic latent subspace ana…
Learning Foreground-Background Segmentation from Improved Layered GANs
Yu Yang, Hakan Bilen, Qiran Zou +2
Deep learning approaches heavily rely on high-quality human supervision which is nonetheless expensive, time-consuming, and error-prone, especially for image segmentation task. In…
Dynamic Filtering with Large Sampling Field for ConvNets
Jialin Wu, Dai Li, Yu Yang +2
We propose a dynamic filtering strategy with large sampling field for ConvNets (LS-DFN), where the position-specific kernels learn from not only the identical position but also mul…