385 citations · 1.3k across the 58 of their papers we have counts for
13 papers · 2 filters
3D-aware Image Synthesis via Learning Structural and Textural Representations
Yinghao Xu, Sida Peng, Ceyuan Yang +2
Making generative models 3D-aware bridges the 2D image space and the 3D physical world yet remains challenging. Recent attempts equip a Generative Adversarial Network (GAN) with a…
Cross-Model Pseudo-Labeling for Semi-Supervised Action Recognition
Yinghao Xu, Fangyun Wei, Xiao Sun +5
Semi-supervised action recognition is a challenging but important task due to the high cost of data annotation. A common approach to this problem is to assign unlabeled data with p…
Improving GAN Equilibrium by Raising Spatial Awareness
Jianyuan Wang, Ceyuan Yang, Yinghao Xu +3
The success of Generative Adversarial Networks (GANs) is largely built upon the adversarial training between a generator (G) and a discriminator (D). They are expected to reach a c…
One-Shot Generative Domain Adaptation
Ceyuan Yang, Yujun Shen, Zhiyi Zhang +4
This work aims at transferring a Generative Adversarial Network (GAN) pre-trained on one image domain to a new domain referring to as few as just one target image. The main challen…
The Nuts and Bolts of Adopting Transformer in GANs
Rui Xu, Xiangyu Xu, Kai Chen +2
Transformer becomes prevalent in computer vision, especially for high-level vision tasks. However, adopting Transformer in the generative adversarial network (GAN) framework is sti…
Interpreting Generative Adversarial Networks for Interactive Image Generation
Bolei Zhou
Significant progress has been made by the advances in Generative Adversarial Networks (GANs) for image generation. However, there lacks enough understanding of how a realistic imag…