58 citations · 93 across the 10 of their papers we have counts for
10 papers
Articulated Kinematics Distillation from Video Diffusion Models
Xuan Li, Qianli Ma, Tsung-Yi Lin +4
We present Articulated Kinematics Distillation (AKD), a framework for generating high-fidelity character animations by merging the strengths of skeleton-based animation and modern…
Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator
Kaiwen Zheng, Yongxin Chen, Huayu Chen +4
While likelihood-based generative models, particularly diffusion and autoregressive models, have achieved remarkable fidelity in visual generation, the maximum likelihood estimatio…
Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling
Kaiwen Zheng, Yongxin Chen, Hanzi Mao +3
Masked diffusion models (MDMs) have emerged as a popular research topic for generative modeling of discrete data, thanks to their superior performance over other discrete diffusion…
Improved Order Analysis and Design of Exponential Integrator for Diffusion Models Sampling
Qinsheng Zhang, Jiaming Song, Yongxin Chen
Efficient differential equation solvers have significantly reduced the sampling time of diffusion models (DMs) while retaining high sampling quality. Among these solvers, exponenti…
DiffCollage: Parallel Generation of Large Content with Diffusion Models
Qinsheng Zhang, Jiaming Song, Xun Huang +2
We present DiffCollage, a compositional diffusion model that can generate large content by leveraging diffusion models trained on generating pieces of the large content. Our approa…
An optimal control approach to particle filtering on Lie groups
Bo Yuan, Qinsheng Zhang, Yongxin Chen
We study the filtering problem over a Lie group that plays an important role in robotics and aerospace applications. We present a new particle filtering algorithm based on stochast…
gDDIM: Generalized denoising diffusion implicit models
Qinsheng Zhang, Molei Tao, Yongxin Chen
Our goal is to extend the denoising diffusion implicit model (DDIM) to general diffusion models~(DMs) besides isotropic diffusions. Instead of constructing a non-Markov noising pro…
Fast Sampling of Diffusion Models with Exponential Integrator
Qinsheng Zhang, Yongxin Chen
The past few years have witnessed the great success of Diffusion models~(DMs) in generating high-fidelity samples in generative modeling tasks. A major limitation of the DM is its…
Path Integral Sampler: a stochastic control approach for sampling
Qinsheng Zhang, Yongxin Chen
We present Path Integral Sampler~(PIS), a novel algorithm to draw samples from unnormalized probability density functions. The PIS is built on the Schrödinger bridge problem which…
Diffusion Normalizing Flow
Qinsheng Zhang, Yongxin Chen
We present a novel generative modeling method called diffusion normalizing flow based on stochastic differential equations (SDEs). The algorithm consists of two neural SDEs: a forw…