61 citations · 350 across the 65 of their papers we have counts for
7 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…
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…
Learning Object-Compositional Neural Radiance Field for Editable Scene Rendering
Bangbang Yang, Yinda Zhang, Yinghao Xu +5
Implicit neural rendering techniques have shown promising results for novel view synthesis. However, existing methods usually encode the entire scene as a whole, which is generally…
CompConv: A Compact Convolution Module for Efficient Feature Learning
Chen Zhang, Yinghao Xu, Yujun Shen
Convolutional Neural Networks (CNNs) have achieved remarkable success in various computer vision tasks but rely on tremendous computational cost. To solve this problem, existing ap…
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…
Decorating Your Own Bedroom: Locally Controlling Image Generation with Generative Adversarial Networks
Chen Zhang, Yinghao Xu, Yujun Shen
Generative Adversarial Networks (GANs) have made great success in synthesizing high-quality images. However, how to steer the generation process of a well-trained GAN model and cus…