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Face detection is a very important task and a necessary pre-processing stepfor many applications such as facial landmark detection, pose estimation,sentiment analysis and face recognition. Not only is face detection animportant pre-processing step in computer vision applications but also incomputational psychology, behavioral imaging and other fields where researchersmight not be initiated in computer vision frameworks and state-of-the-artdetection applications. A large part of existing research that includes facedetection as a pre-processing step uses existing out-of-the-box detectors suchas the HoG-based dlib and the OpenCV Haar face detector which are no longerstate-of-the-art - they are primarily used because of their ease of use andaccessibility. We introduce Dockerface, a very accurate Faster R-CNN facedetector in a Docker container which requires no training and is easy toinstall and use.

Dockerface: an Easy to Install and Use Faster R-CNN Face Detector in a Docker Container