乐胖代购免代理版

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However, the low sample counts at real\u2010time framerates bring enormous challenges to existing path sampling methods. Recent work (ReSTIR GI) samples indirect illumination effectively with a dramatic bias reduction. However, as a screen\u2010space based path resampling approach, it can only reuse the path at the first bounce and brings subtle benefits for complex scenes. To this end, we propose a world\u2010space based spatiotemporal path resampling approach. Our approach caches more path samples into a world\u2010space grid, which allows reusing sub\u2010path starting from non\u2010primary path vertices. Furthermore, we introduce a practical normal\u2010aware hash grid construction approach, providing more efficient candidate samples for path resampling. 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