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Facial expression recognition, classification 2006 [112] Binghamton University: Face Recognition Grand Challenge Dataset Up to 22 samples for each subject. Expressions: anger, happiness, sadness, surprise, disgust, puffy. 3D Data. None. 4007 Images, text Face recognition, classification 2004 [113] [114] National Institute of Standards and ...
The Facial Recognition Technology (FERET) database is a dataset used for facial recognition system evaluation as part of the Face Recognition Technology (FERET) program.It was first established in 1993 under a collaborative effort between Harry Wechsler at George Mason University and Jonathon Phillips at the Army Research Laboratory in Adelphi, Maryland.
A facial expression database is a collection of images or video clips with facial expressions of a range of emotions. Well-annotated ( emotion -tagged) media content of facial behavior is essential for training, testing, and validation of algorithms for the development of expression recognition systems .
DeepFace is a deep learning facial recognition system created by a research group at Facebook.It identifies human faces in digital images. The program employs a nine-layer neural network with over 120 million connection weights and was trained on four million images uploaded by Facebook users.
For further details check the project's GitHub repository or the Hugging Face dataset cards (taskmaster-1, taskmaster-2, taskmaster-3). Dialog/Instruction prompted 2019 [339] Byrne and Krishnamoorthi et al. DrRepair A labeled dataset for program repair. Pre-processed data Check format details in the project's worksheet. Dialog/Instruction prompted
This method trains a facial recognition software using already altered images. This results in the software not being able to match the altered image with the actual image, as it does not recognize them as the same image. Fawkes also uses data poisoning attacks, which change the data set used to train certain deep learning models. Fawkes ...
Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]
Eigenface provides an easy and cheap way to realize face recognition in that: Its training process is completely automatic and easy to code. Eigenface adequately reduces statistical complexity in face image representation. Once eigenfaces of a database are calculated, face recognition can be achieved in real time.