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S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017
S³FD (Single Shot Scale-invariant Face Detector) is a real-time face detection framework designed to handle faces of various sizes with high accuracy using a single deep neural network. Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research.
Tested, portable, standard C++ source code for policy based log stream, configuration data, external string table, field-delimited strings and text file reader. BSD license. Templated for use with any valid instantiation of std::basic_string.