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title
Learning to Facrtorize and Relight a City (ECCV 2020)
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Project Page for Learning to Factorize and Relight a City. ECCV 2020
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Andrew
updated
2025-12-20 18:32:49
raw text
Learning to Factorize and Relight a City Paper Video Slides Code Supplementary Learning to Factorize and Relight a City ECCV 2020 Andrew Liu Shiry Ginosar Tinghui Zhou Alexei A. Efros Noah Snavely Google UC Berkeley Humen AI UC Berkeley Google [Paper] [Code] [Additional Results] Abstract We propose a learning-based framework for disentangling outdoor scenes into temporally-varying illumination and permanent scene factors. Inspired by the classic intrinsic image decomposition, our learning signal builds upon two insights: 1) combining the disentangled factors should reconstruct the original image, and 2) the permanent factors should stay constant across multiple temporal samples of the same scene. To facilitate training, we assemble a city-scale dataset of outdoor timelapse imagery from Google Street View, where the same locations are captured repeatedly through time. This data represents an unprecedented scale of spati...
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