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We introduce a new algorithm---ReSTIR---that renders such lighting interactively, at high quality, and without needing to maintain complex data structures. We repeatedly resample a set of candidate light samples and apply further spatial and temporal resampling to leverage information from relevant nearby samples. We derive an unbiased Monte Carlo estimator for this approach, and show that it achieves equal-error 6\u00d7-60\u00d7 faster than state-of-the-art methods. A biased estimator reduces noise further and is 35\u00d7-65\u00d7 faster, at the cost of some energy loss. 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