From the 1 of 5 linked papers with an AI index.
5 papers
MoLingo: Motion-Language Alignment for Text-to-Human Motion Generation
Yannan He, Garvita Tiwari, Xiaohan Zhang +4
MoLingo is a model that generates realistic human motion from textual descriptions by using a semantically aligned latent space and cross‑attention conditioning during diffusion.
GIRAF: Towards Generalizable Human Interactions with Articulated Objects
Xiaohan Zhang, Sebastian Starke, Alexander Winkler +3
Synthesizing realistic full-body human interactions with articulated objects is a fundamental challenge for embodied AI and graphics, with applications in robotics training and vir…
AeSlides: Incentivizing Aesthetic Layout in LLM-Based Slide Generation via Verifiable Rewards
Yiming Pan, Chengwei Hu, Xuancheng Huang +6
Large language models (LLMs) have demonstrated strong potential in agentic tasks, particularly in slide generation. However, slide generation poses a fundamental challenge: the gen…
SCENIC: Scene-aware Semantic Navigation with Instruction-guided Control
Xiaohan Zhang, Sebastian Starke, Vladimir Guzov +3
Synthesizing natural human motion that adapts to complex environments while allowing creative control remains a fundamental challenge in motion synthesis. Existing models often fal…
FORCE: Physics-aware Human-object Interaction
Xiaohan Zhang, Bharat Lal Bhatnagar, Sebastian Starke +5
Interactions between human and objects are influenced not only by the object's pose and shape, but also by physical attributes such as object mass and surface friction. They introd…