This is an introduction to the face detection of technology from the view of the article:
"2016 ACM MM unitbox:an Advanced Object Detection Network".
The code should not be put out, but the implementation is relatively simple. (Interrupt a sentence, the paper said speed can reach 12fps, I'm a little panic, we look at science does not) —————————— split line ——————
human face recognition in vivo detection
In biometric systems, in order to prevent malicious people from forging and stealing other people's biological characteristics for identity authentication, biometric systems need to have a live detection function, that is, to determine whether the submitted biological characteristics come from living individuals.
In vivo
This article is reproduced from: https://blog.csdn.net/shuzfan/article/details/52625449
This is an introduction to the face detection of technology from the view of the article:
"2016 ACM MM unitbox:an Advanced Object Detection Network".
The code should not be put out, but the implementation is relatively simple. (Interrupt a sentence, the paper said speed can re
Grid loss:detecting occluded FacesECCV2016
The problem of occlusion is to be solved by area chunking.
For the occlusion of face detection, it is more difficult to solve this problem from the angle of training data. We solve this problem from the point of view of defining a new loss function. By defining a novel loss layer to block the loss of face counting error,
This article mainly introduces the use of Google's own facedetectionlistener for face detection, and the detection of the face with a rectangular frame drawn out. This code is based on PlayCameraV1.0.0 and has been changed on the camera's open and preview processes. Originally placed in a separate thread, this time I p
First of all, has been considering such a great opencv should change some of the outdated things, such as: detectors, recognizers and so on, sure enough, openv the big guys or secretly changed.
Direct load Caffe Depth learning (SSD face detection) model has been OPENCV: (a powerful one)
Here's the Python code:
Use Picture:
Python detect_faces.py--image rooster.jpg--prototxt deploy.prototxt.txt--model. Caffe
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