119 citations · 287 across the 16 of their papers we have counts for
5 papers · 2 filters
Manifold-valued Image Generation with Wasserstein Generative Adversarial Nets
Zhiwu Huang, Jiqing Wu, Luc Van Gool
Generative modeling over natural images is one of the most fundamental machine learning problems. However, few modern generative models, including Wasserstein Generative Adversaria…
Wasserstein Divergence for GANs
Jiqing Wu, Zhiwu Huang, Janine Thoma +2
In many domains of computer vision, generative adversarial networks (GANs) have achieved great success, among which the family of Wasserstein GANs (WGANs) is considered to be state…
Improving Video Generation for Multi-functional Applications
Bernhard Kratzwald, Zhiwu Huang, Danda Pani Paudel +2
In this paper, we aim to improve the state-of-the-art video generative adversarial networks (GANs) with a view towards multi-functional applications. Our improved video GAN model d…
Sliced Wasserstein Generative Models
Jiqing Wu, Zhiwu Huang, Dinesh Acharya +4
In generative modeling, the Wasserstein distance (WD) has emerged as a useful metric to measure the discrepancy between generated and real data distributions. Unfortunately, it is…
On the Relation between Color Image Denoising and Classification
Jiqing Wu, Radu Timofte, Zhiwu Huang +1
Large amount of image denoising literature focuses on single channel images and often experimentally validates the proposed methods on tens of images at most. In this paper, we inv…