12 citations · 30 across the 7 of their papers we have counts for
7 papers
BerfScene: Bev-conditioned Equivariant Radiance Fields for Infinite 3D Scene Generation
Qihang Zhang, Yinghao Xu, Yujun Shen +3
Generating large-scale 3D scenes cannot simply apply existing 3D object synthesis technique since 3D scenes usually hold complex spatial configurations and consist of a number of o…
Learning Modulated Transformation in GANs
Ceyuan Yang, Qihang Zhang, Yinghao Xu +3
The success of style-based generators largely benefits from style modulation, which helps take care of the cross-instance variation within data. However, the instance-wise stochast…
Improving GANs with A Dynamic Discriminator
Ceyuan Yang, Yujun Shen, Yinghao Xu +3
Discriminator plays a vital role in training generative adversarial networks (GANs) via distinguishing real and synthesized samples. While the real data distribution remains the sa…
Learning Hierarchical Cross-Modal Association for Co-Speech Gesture Generation
Xian Liu, Qianyi Wu, Hang Zhou +7
Generating speech-consistent body and gesture movements is a long-standing problem in virtual avatar creation. Previous studies often synthesize pose movement in a holistic manner,…
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…
Safe Exploration by Solving Early Terminated MDP
Hao Sun, Ziping Xu, Meng Fang +4
Safe exploration is crucial for the real-world application of reinforcement learning (RL). Previous works consider the safe exploration problem as Constrained Markov Decision Proce…
Overcoming Catastrophic Forgetting by Generative Regularization
Patrick H. Chen, Wei Wei, Cho-jui Hsieh +1
In this paper, we propose a new method to overcome catastrophic forgetting by adding generative regularization to Bayesian inference framework. Bayesian method provides a general f…