most citedAdversarially Approximated Autoencoder for Image Generation and Manipulation

6 citations · 18 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20216 cited

DRB-GAN: A Dynamic ResBlock Generative Adversarial Network for Artistic Style Transfer

Wenju Xu, Chengjiang Long, Ruisheng Wang +1

The paper proposes a Dynamic ResBlock Generative Adversarial Network (DRB-GAN) for artistic style transfer. The style code is modeled as the shared parameters for Dynamic ResBlocks…

cs.CV20214 cited

Dual Graph Convolutional Networks with Transformer and Curriculum Learning for Image Captioning

Xinzhi Dong, Chengjiang Long, Wenju Xu +1

Existing image captioning methods just focus on understanding the relationship between objects or instances in a single image, without exploring the contextual correlation existed…

cs.RO2019

Direct Visual-Inertial Odometry with Semi-Dense Mapping

Wenju Xu, Dongkyu Choi, Guanghui Wang

The paper presents a direct visual-inertial odometry system. In particular, a tightly coupled nonlinear optimization based method is proposed by integrating the recent advances in…

cs.CV2019

Toward Learning a Unified Many-to-Many Mapping for Diverse Image Translation

Wenju Xu, Shawn Keshmiri, Guanghui Wang

Image-to-image translation, which translates input images to a different domain with a learned one-to-one mapping, has achieved impressive success in recent years. The success of t…

cs.LG20192 cited

Time-Delay Momentum: A Regularization Perspective on the Convergence and Generalization of Stochastic Momentum for Deep Learning

Ziming Zhang, Wenju Xu, Alan Sullivan

In this paper we study the problem of convergence and generalization error bound of stochastic momentum for deep learning from the perspective of regularization. To do so, we first…

cs.LG20196 cited

Adversarially Approximated Autoencoder for Image Generation and Manipulation

Wenju Xu, Shawn Keshmiri, Guanghui Wang

Regularized autoencoders learn the latent codes, a structure with the regularization under the distribution, which enables them the capability to infer the latent codes given obser…