A new paper proposes a framework to advance visual generation models beyond photorealism towards intelligent systems capable of understanding structure, causality, and long-term consistency. The authors introduce a five-level taxonomy, from Atomic Generation to World-Modeling Generation, to categorize these advancements. The paper also analyzes key technical drivers and critiques current evaluation methods, suggesting a capability-centered approach for future development. AI
影响 Proposes a new taxonomy and evaluation framework for advancing visual generation capabilities beyond current limitations.
排序理由 Academic paper proposing a new taxonomy and roadmap for visual generation models.
- Agentic Generation
- arXiv
- Atomic Generation
- Computer Science
- In-Context Generation
- World-Modeling Generation
- Conditional Generation
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