{"slug": "giraf-towards-generalizable-human-interactions-with-articulated-objects", "title": "GIRAF: Towards Generalizable Human Interactions with Articulated Objects", "summary": "Researchers introduced GIRAF, a text-conditioned diffusion model that generates realistic full-body human interactions with articulated objects, addressing limitations of prior work focused on static objects or hand-only manipulation. The model uses an object-centric representation, mixed-domain training, and contact-based augmentation to generalize across diverse object positions and shapes, outperforming current state-of-the-art methods.", "body_md": "arXiv:2607.07880v1 Announce Type: new\nAbstract: Synthesizing realistic full-body human interactions with articulated objects is a fundamental challenge for embodied AI and graphics, with applications in robotics training and virtual agents. Existing models remain limited: some focus on simple activities with static objects, while others restrict attention to hand-only manipulation. This leaves open the problem of generating coordinated full-body motion that approaches, manipulates, and moves articulated objects in a realistic and generalizable way. The key difficulty lies in reasoning jointly about locomotion, fine-grained contact, and object articulation. Models must capture subtle hand-object correspondences that transfer across object geometries, while also producing seamless transitions from navigation to manipulation. At the same time, the scarcity of large-scale paired motion-scene data makes it difficult to generalize across diverse object positions and shapes. We introduce a text-conditioned diffusion model that addresses these challenges through three core ideas: an object-centric representation that unifies hand-object contact with object surfaces, a mixed-domain training strategy that balances locomotion and interaction, and a contact-based augmentation scheme that expands training diversity. Through experiments, our method demonstrated strong generalization to unseen object configurations, surpassing current state-of-the-art methods.", "url": "https://wpnews.pro/news/giraf-towards-generalizable-human-interactions-with-articulated-objects", "canonical_source": "https://arxiv.org/abs/2607.07880", "published_at": "2026-07-10 04:00:00+00:00", "updated_at": "2026-07-10 04:21:27.545446+00:00", "lang": "en", "topics": ["artificial-intelligence", "computer-vision", "generative-ai", "robotics"], "entities": [], "alternates": {"html": "https://wpnews.pro/news/giraf-towards-generalizable-human-interactions-with-articulated-objects", "markdown": "https://wpnews.pro/news/giraf-towards-generalizable-human-interactions-with-articulated-objects.md", "text": "https://wpnews.pro/news/giraf-towards-generalizable-human-interactions-with-articulated-objects.txt", "jsonld": "https://wpnews.pro/news/giraf-towards-generalizable-human-interactions-with-articulated-objects.jsonld"}}