85 citations · 482 across the 58 of their papers we have counts for
6 papers · 1 filter
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…
Data-Efficient Instance Generation from Instance Discrimination
Ceyuan Yang, Yujun Shen, Yinghao Xu +1
Generative Adversarial Networks (GANs) have significantly advanced image synthesis, however, the synthesis quality drops significantly given a limited amount of training data. To i…
Instance Localization for Self-supervised Detection Pretraining
Ceyuan Yang, Zhirong Wu, Bolei Zhou +1
Prior research on self-supervised learning has led to considerable progress on image classification, but often with degraded transfer performance on object detection. The objective…