3 papers
cs.CV2026
Language-Guided Transformer Tokenizer for Human Motion Generation
Sheng Yan, Yong Wang, Xin Du +2
In this paper, we focus on motion discrete tokenization, which converts raw motion into compact discrete tokens--a process proven crucial for efficient motion generation. In this p…
cs.CV2026
SSR: Pushing the Limit of Spatial Intelligence with Structured Scene Reasoning
Yi Zhang, Youya Xia, Yong Wang +7
While Multimodal Large Language Models (MLLMs) excel in semantic tasks, they frequently lack the "spatial sense" essential for sophisticated geometric reasoning. Current models typ…
cs.CV2025
MoSa: Motion Generation with Scalable Autoregressive Modeling
Mengyuan Liu, Sheng Yan, Yong Wang +3
We introduce MoSa, a novel hierarchical motion generation framework for text-driven 3D human motion generation that enhances the Vector Quantization-guided Generative Transformers…