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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.
The project aims to be the repository for commonly used routines within the FreeDOS project, to help developers make it easier to develop and reuse code that is better proved and follows the FreeDOS standards.