most citedLearning to Annotate Part Segmentation with Gradient Matching

4 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20224 cited

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.…

cs.CV2022

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…

cs.CV2022

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…

cs.CV20222 cited

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…

cs.CV2018

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…