给AI指定任意颜色，精确到十六进制
以前让AI生成或修改图片里的物体颜色，你只能说“红色”“深蓝”这种模糊词，或者从预设色板里挑。这篇让AI听懂精确到十六进制的颜色代码，比如#FF5733，而且生成和编辑共用同一套指令。做法是：先给模型看大量“物体+精确颜色”的配对数据，再用纯色块校准阴影带来的误差。在FLUX.2-4B上，生成和编辑的精确配色得分分别提升85.3%和28.3%。它不是你明天就能用的产品，但这是AI从“会画”走向“按规格画”的关键一步——设计师、电商、品牌物料这些对颜色有硬性要求的场景，是它最终要服务的地方。
📄 原文摘要(英文)
Professional design requires any-color control: the ability to specify an object's target color with any 24-bit hex value for image generation and editing. Prior work has explored color generation, editing, and colorization, but often relies on dedicated color representations or specialized inference procedures. Advances in large language models offer a simpler starting point: even compact models can associate hex values with color semantics. We present Paint-Anything, which learns a shared hex-prompt interface for generation and editing through object-level color supervision. We develop a data pipeline that constructs Paint-500K from real images through object grounding, perceptual color labeling, and editing-pair synthesis. Since shadows make real-image labels only approximate colors, we complement this supervision with pure-color anchors whose pixels exactly match their paired hex values. These anchors are used only at high-noise timesteps, leaving low-noise training to natural images. We further introduce Any Color Benchmark (ACBench), comprising ACBench-T2I and ACBench-Edit, to measure object-level hex color fidelity across both tasks. On FLUX.2-4B, Paint-Anything improves ACBench-T2I and ACBench-Edit scores by 85.3% and 28.3%, respectively, relative to the base model, with ablations supporting the training recipe. It also achieves the highest average CompColor score among the compared methods.