110 citations · 124 across the 7 of their papers we have counts for
7 papers
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…
Multiclass Learning from Noisy Labels for Non-decomposable Performance Measures
Mingyuan Zhang, Shivani Agarwal
There has been much interest in recent years in learning good classifiers from data with noisy labels. Most work on learning from noisy labels has focused on standard loss-based pe…
Multi-scale 2D Temporal Map Diffusion Models for Natural Language Video Localization
Chongzhi Zhang, Mingyuan Zhang, Zhiyang Teng +5
Natural Language Video Localization (NLVL), grounding phrases from natural language descriptions to corresponding video segments, is a complex yet critical task in video understand…
InsActor: Instruction-driven Physics-based Characters
Jiawei Ren, Mingyuan Zhang, Cunjun Yu +3
Generating animation of physics-based characters with intuitive control has long been a desirable task with numerous applications. However, generating physically simulated animatio…
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…
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…