40 citations · 145 across the 19 of their papers we have counts for
7 papers · 1 filter
Cycle In Cycle Generative Adversarial Networks for Keypoint-Guided Image Generation
Hao Tang, Dan Xu, Gaowen Liu +3
In this work, we propose a novel Cycle In Cycle Generative Adversarial Network (CGAN) for the task of keypoint-guided image generation. The proposed CGAN is a cross-modal f…
Cascade Attention Guided Residue Learning GAN for Cross-Modal Translation
Bin Duan, Wei Wang, Hao Tang +2
Since we were babies, we intuitively develop the ability to correlate the input from different cognitive sensors such as vision, audio, and text. However, in machine learning, this…
Backpropagation-Friendly Eigendecomposition
Wei Wang, Zheng Dang, Yinlin Hu +2
Eigendecomposition (ED) is widely used in deep networks. However, the backpropagation of its results tends to be numerically unstable, whether using ED directly or approximating it…
Recurrent U-Net for Resource-Constrained Segmentation
Wei Wang, Kaicheng Yu, Joachim Hugonot +2
State-of-the-art segmentation methods rely on very deep networks that are not always easy to train without very large training datasets and tend to be relatively slow to run on sta…
Expression Conditional GAN for Facial Expression-to-Expression Translation
Hao Tang, Wei Wang, Songsong Wu +4
In this paper, we focus on the facial expression translation task and propose a novel Expression Conditional GAN (ECGAN) which can learn the mapping from one image domain to anothe…
Dual Generator Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
Hao Tang, Dan Xu, Wei Wang +2
State-of-the-art methods for image-to-image translation with Generative Adversarial Networks (GANs) can learn a mapping from one domain to another domain using unpaired image data.…