ATLAS: A Unified MLLM Framework for Layout-Aware Controllable Image Generation
Researchers have introduced ATLAS, a unified multimodal large language model (MLLM) framework that employs a 'Think, Plan, and Paint' approach for controllable image generation. By using layout as a shared representation, ATLAS enables improved spatial reasoning, explicit object arrangement planning, and high-fidelity image rendering. The model achieves state-of-the-art results on image generation benchmarks, with a reported 65.31% improvement over previous layout-based unified MLLMs and notable gains on spatial reasoning tasks. ATLAS also supports instruction-guided editing and multimodal grounding through its layout interface.
Why it matters: ATLAS advances the controllability and spatial reasoning capabilities of unified MLLMs, addressing a key limitation in current image generation models.
Full story at: arXiv Computer Vision ↗