most citedCASE: Learning Conditional Adversarial Skill Embeddings for Physics-based Characters

39 citations · 59 across the 6 of their papers we have counts for

collaborators

6 papers

cs.GR2024

CT4D: Consistent Text-to-4D Generation with Animatable Meshes

Ce Chen, Shaoli Huang, Xuelin Chen +4

Text-to-4D generation has recently been demonstrated viable by integrating a 2D image diffusion model with a video diffusion model. However, existing models tend to produce results…

cs.GR2024

Taming Diffusion Probabilistic Models for Character Control

Rui Chen, Mingyi Shi, Shaoli Huang +3

We present a novel character control framework that effectively utilizes motion diffusion probabilistic models to generate high-quality and diverse character animations, responding…

cs.CV202319 cited

SweetDreamer: Aligning Geometric Priors in 2D Diffusion for Consistent Text-to-3D

Weiyu Li, Rui Chen, Xuelin Chen +1

It is inherently ambiguous to lift 2D results from pre-trained diffusion models to a 3D world for text-to-3D generation. 2D diffusion models solely learn view-agnostic priors and t…

cs.GR202339 cited

CASE: Learning Conditional Adversarial Skill Embeddings for Physics-based Characters

Zhiyang Dou, Xuelin Chen, Qingnan Fan +2

We present CASE, an efficient and effective framework that learns conditional Adversarial Skill Embeddings for physics-based characters. Our physically simulated character c…

cs.CV20231 cited

LivelySpeaker: Towards Semantic-Aware Co-Speech Gesture Generation

Yihao Zhi, Xiaodong Cun, Xuelin Chen +4

Gestures are non-verbal but important behaviors accompanying people's speech. While previous methods are able to generate speech rhythm-synchronized gestures, the semantic context…

cs.GR2023

Patch-based 3D Natural Scene Generation from a Single Example

Weiyu Li, Xuelin Chen, Jue Wang +1

We target a 3D generative model for general natural scenes that are typically unique and intricate. Lacking the necessary volumes of training data, along with the difficulties of h…