Compositional SVG Generation via VLM-Driven Hierarchical Semantic Parsing
This work proposes a VLM-driven agentic framework for semantic compositional SVG generation that recursively parses visual scenes into semantic and geometric hierarchies via top-down decomposition, visual grounding, and prompt-driven amodal occlusion recovery, ensuring each component is geometrically complete.
Sehwan Park, Taehoon Kim, Geonhee Han et al.
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