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Pat Hanrahan

2 accepted papers

2017

Submodular Trajectory Optimization for Aerial 3D Scanning

ICCV 2017poster

Drones equipped with cameras are emerging as a powerful tool for large-scale aerial 3D scanning, but existing automatic flight planners do not exploit all available information about the scene, and can therefore produce inaccurate and incomplete 3D models. We present an automatic method to generate…

Cited by 177PDFScholar
2016

Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs using Neural Networks

NeurIPS 2016poster

Probabilistic inference algorithms such as Sequential Monte Carlo (SMC) provide powerful tools for constraining procedural models in computer graphics, but they require many samples to produce desirable results. In this paper, we show how to create procedural models which learn how to satisfy constr…