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Today's visual generation models excel at photorealism but still fail at the kind of spatial reasoning, long-term consistency, and causal understanding that truly intelligent visual generation demands.
Simply throwing more data at your pavement distress detection model isn't enough; carefully controlling for illumination and spatial variations during training can boost accuracy by over 9% and improve long-term consistency.
