刘年丰：操作的核心是操作对象，但以前的主流模型太关注全局信息。我们的思路是：通过多个二维热力图，把要操作的对象位置自适应地学习出来，让模型意识到什么是最需要响应的操作对象。
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For example, a 500km route might be broken down into ~100 such shortcuts. If each A* shortcut calculation explores 100-1000 detailed road segments, the total detailed segments visited by A* might be around 10,000-50,000. Compare this to the 1,000,000+ segments the old A* might have needed for the entire route!
Most digital images intended for viewing are generally assumed to be in sRGB colour space, which is gamma-encoded. This means that a linear increase of value in colour space does not correspond to a linear increase in actual physical light intensity, instead following more of a curve. If we want to mathematically operate on colour values in a physically accurate way, we must first convert them to linear space by applying gamma decompression. After processing, gamma compression should be reapplied before display. The following C code demonstrates how to do so following the sRGB standard: