Stacked sequential scale-space taylor context
C. Gatta and F. Ciompi
IEEE Transactions on Pattern Analysis and Machine Intelligence (2014)
We analyze sequential image labeling methods that sample the posterior label field in order to gather contextual information. We propose an effective method that extracts local Taylor coefficients from the posterior at different scales. Results show that our proposal outperforms state-of-the-art methods on MSRC-21, CAMVID, eTRIMS8 and KAIST2 data sets.
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