7 papers
MotionRFT: Unified Reinforcement Fine-Tuning for Text-to-Motion Generation
Xiaofeng Tan, Wanjiang Weng, Hongsong Wang +3
Text-to-motion generation has advanced with diffusion- and flow-based generative models, yet supervised pretraining remains insufficient to align models with high-level objectives…
Bilingual Text-to-Motion Generation: A New Benchmark and Baselines
Wanjiang Weng, Xiaofeng Tan, Xiangbo Shu +3
Text-to-motion generation holds significant potential for cross-linguistic applications, yet it is hindered by the lack of bilingual datasets and the poor cross-lingual semantic un…
EasyTune: Efficient Step-Aware Fine-Tuning for Diffusion-Based Motion Generation
Xiaofeng Tan, Wanjiang Weng, Haodong Lei +1
In recent years, motion generative models have undergone significant advancement, yet pose challenges in aligning with downstream objectives. Recent studies have shown that using d…
ReAlign: Text-to-Motion Generation via Step-Aware Reward-Guided Alignment
Wanjiang Weng, Xiaofeng Tan, Junbo Wang +3
Text-to-motion generation, which synthesizes 3D human motions from text inputs, holds immense potential for applications in gaming, film, and robotics. Recently, diffusion-based me…
Foundation Model for Skeleton-Based Human Action Understanding
Hongsong Wang, Wanjiang Weng, Junbo Wang +4
Human action understanding serves as a foundational pillar in the field of intelligent motion perception. Skeletons serve as a modality- and device-agnostic representation for huma…
ReAlign: Bilingual Text-to-Motion Generation via Step-Aware Reward-Guided Alignment
Wanjiang Weng, Xiaofeng Tan, Hongsong Wang +1
Bilingual text-to-motion generation, which synthesizes 3D human motions from bilingual text inputs, holds immense potential for cross-linguistic applications in gaming, film, and r…