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20222026
most citedMotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model

110 citations · 112 across the 10 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024

CrowdMoGen: Zero-Shot Text-Driven Collective Motion Generation

Yukang Cao, Xinying Guo, Mingyuan Zhang +3

While recent advances in text-to-motion generation have shown promising results, they typically assume all individuals are grouped as a single unit. Scaling these methods to handle…

cs.CV2024

Large Motion Model for Unified Multi-Modal Motion Generation

Mingyuan Zhang, Daisheng Jin, Chenyang Gu +8

Human motion generation, a cornerstone technique in animation and video production, has widespread applications in various tasks like text-to-motion and music-to-dance. Previous wo…

cs.CV2023

Digital Life Project: Autonomous 3D Characters with Social Intelligence

Zhongang Cai, Jianping Jiang, Zhongfei Qing +20

In this work, we present Digital Life Project, a framework utilizing language as the universal medium to build autonomous 3D characters, who are capable of engaging in social inter…

cs.CV2023★ 2 cited

ReMoDiffuse: Retrieval-Augmented Motion Diffusion Model

Mingyuan Zhang, Xinying Guo, Liang Pan +5

3D human motion generation is crucial for creative industry. Recent advances rely on generative models with domain knowledge for text-driven motion generation, leading to substanti…

cs.CV2022★ 110 cited

MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model

Mingyuan Zhang, Zhongang Cai, Liang Pan +4

Human motion modeling is important for many modern graphics applications, which typically require professional skills. In order to remove the skill barriers for laymen, recent moti…