Python wrapper to Philipp Krähenbühl's dense (fully connected) CRFs with gaussian edge potentials.
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Updated
Mar 5, 2024 - C++
Python wrapper to Philipp Krähenbühl's dense (fully connected) CRFs with gaussian edge potentials.
machine learning algorithm
Named Entity Recognition (NER) models (neural and sparse) implemented based on package LibN3L
C++ based implementation of StatNLP framework
Customized summarization of egocentric videos as described in "Active Video Summarization: Customized Summaries via On-line Interaction with the User." AAAI. 2017.
UNet with CRF-as-RNN layer
轻量级中文分词系统(Lightweight Chinese Segmentation)
nxtgm -- a C++/Python/JavaScript library for discrete graphical models writen in C++17
GitHub archive of Philipp Krähenbühl's dense CRF code
Dense Random Fields http://graphics.stanford.edu/projects/drf/learning.pdf
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