Research focus
About the research
How can visual systems identify materials and lighting from photographs to enable realistic editing and recognition?
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The group develops datasets and algorithms for material recognition and visual search, including the Materials in Context Database and visual similarity models. Researchers build physically-based and differentiable rendering methods for recovering shape and material properties to support editing and relighting. The group applies remote-sensing and scale-aware recognition techniques to satellite imagery and cloud removal benchmarks for Earth-observation tasks. Methods combine convolutional neural networks, differentiable Monte Carlo rendering, and dataset/benchmark construction to evaluate recognition and inverse-rendering performance.
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