FaV-A generates positive-negative space compositions via a staged multimodal agent, with experiments and ablations suggesting gains over direct zero-shot MLLM baselines
The work presents Form and Void Agent (FaV-A), a multimodal agent for staged positive-negative space generation: it first generates a base object, then analyzes its shape and spatial structure to identify candidate negative-space semantics, and finally produces compositional instructions for the final image generation stage; experiments and ablation analyses suggest FaV-A yields more visually coherent and semantically aligned positive-negative space compositions than direct zero-shot MLLM baselines.