12 citations · 12 across the 4 of their papers we have counts for
5 papers
Image Diffusion Models Are Good 3D Human Motion Generators
Siyuan Yang, Chong Wang, Hao Cheng +4
Text-to-motion generation typically relies on dataset-specific skeletal representations, with models trained separately for benchmarks with different joint layouts. We investigate…
Skeleton-to-Image Encoding: Enabling Skeleton Representation Learning via Vision-Pretrained Models
Siyuan Yang, Jun Liu, Hao Cheng +5
Recent advances in large-scale pretrained vision models have demonstrated impressive capabilities across a wide range of downstream tasks, including cross-modal and multi-modal sce…
Reconciling Stochastic and Deterministic Strategies for Zero-shot Image Restoration using Diffusion Model in Dual
Chong Wang, Lanqing Guo, Zixuan Fu +4
Plug-and-play (PnP) methods offer an iterative strategy for solving image restoration (IR) problems in a zero-shot manner, using a learned \textit{discriminative denoiser} as the i…
Progressive Divide-and-Conquer via Subsampling Decomposition for Accelerated MRI
Chong Wang, Lanqing Guo, Yufei Wang +3
Deep unfolding networks (DUN) have emerged as a popular iterative framework for accelerated magnetic resonance imaging (MRI) reconstruction. However, conventional DUN aims to recon…
Variational Disentanglement for Domain Generalization
Yufei Wang, Haoliang Li, Hao Cheng +3
Domain generalization aims to learn an invariant model that can generalize well to the unseen target domain. In this paper, we propose to tackle the problem of domain generalizatio…