groundingLMM

★ 969

vs

posecode

★ 123

groundingLMM vs posecode

groundingLMM: GLaMM (Grounding Large Multimodal Model) is an end-to-end trained LMM capable of generating natural language responses integrated with object segmentation masks, enabling visual grounding and versatile interaction with images at multiple granularity levels. It introduces the novel task of Grounded Conversation Generation (GCG), supports various downstream applications like referring expression segmentation and region-level captioning, and is underpinned by the large-scale GranD dataset.; posecode: Posecode is a human-readable spatial domain-specific language (DSL) for describing, validating, and rendering human motion as text. It enables LLMs to express kinematic movements in a structured, programmable, and visually renderable format, offering an alternative to unstructured prose or static diagrams.