46 citations · 86 across the 9 of their papers we have counts for
9 papers
Divide-and-Conquer Adversarial Learning for High-Resolution Image and Video Enhancement
Zhiwu Huang, Danda Pani Paudel, Guanju Li +3
This paper introduces a divide-and-conquer inspired adversarial learning (DACAL) approach for photo enhancement. The key idea is to decompose the photo enhancement process into hie…
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…
Face Translation between Images and Videos using Identity-aware CycleGAN
Zhiwu Huang, Bernhard Kratzwald, Danda Pani Paudel +2
This paper presents a new problem of unpaired face translation between images and videos, which can be applied to facial video prediction and enhancement. In this problem there exi…
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…
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…
Building Deep Networks on Grassmann Manifolds
Zhiwu Huang, Jiqing Wu, Luc Van Gool
Learning representations on Grassmann manifolds is popular in quite a few visual recognition tasks. In order to enable deep learning on Grassmann manifolds, this paper proposes a d…
Generic 3D Convolutional Fusion for image restoration
Jiqing Wu, Radu Timofte, Luc Van Gool
Also recently, exciting strides forward have been made in the area of image restoration, particularly for image denoising and single image super-resolution. Deep learning technique…