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Papers

Structured Regression Gradient Boosting

2016-06-01 · CVPR 2016 6 · Ferran Diego, Fred A. Hamprecht

We propose a new way to train a structured output prediction model. More specifically, we train nonlinear data terms in a Gaussian Conditional Random Field (GCRF) by a generalized version of gradient boosting. The approach is evaluated on three challenging regression benchmarks: vessel detection, single image depth estimation and image inpainting. These experiments suggest that the proposed boosting framework matches or exceeds the state-of-the-art.

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Depth EstimationImage InpaintingregressionVessel Detection

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