activity
20182022
most citedSemantic Hierarchy Emerges in Deep Generative Representations for Scene Synthesis

42 citations · 127 across the 5 of their papers we have counts for

collaborators

12 papers

cs.CV202237 cited

Accelerating Diffusion Models via Early Stop of the Diffusion Process

Zhaoyang Lyu, Xudong XU, Ceyuan Yang +2

Denoising Diffusion Probabilistic Models (DDPMs) have achieved impressive performance on various generation tasks. By modeling the reverse process of gradually diffusing the data d…

cs.CV202131 cited

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…

cs.CV20218 cited

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…

cs.CV2020

Generative Hierarchical Features from Synthesizing Images

Yinghao Xu, Yujun Shen, Jiapeng Zhu +2

Generative Adversarial Networks (GANs) have recently advanced image synthesis by learning the underlying distribution of the observed data. However, how the features learned from s…

cs.CV20209 cited

Unsupervised Landmark Learning from Unpaired Data

Yinghao Xu, Ceyuan Yang, Ziwei Liu +2

Recent attempts for unsupervised landmark learning leverage synthesized image pairs that are similar in appearance but different in poses. These methods learn landmarks by encourag…

cs.CV2020

Video Representation Learning with Visual Tempo Consistency

Ceyuan Yang, Yinghao Xu, Bo Dai +1

Visual tempo, which describes how fast an action goes, has shown its potential in supervised action recognition. In this work, we demonstrate that visual tempo can also serve as a…