PhysMLLMs: Spatial Priors for Unified Referring Segmentation and Grounded Reasoning of Images and Videos
PhysMLLMs is a training-stage prior injection architecture that injects physics-inspired spatial continuity priors into Video MLLMs, demonstrating that the injected spatial prior improves video consistency without compromising image-level grounding or general multimodal capability.
Siyao Yan, Bo Han, Jisheng Dang et al.
· 0 citations