Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Jourabloo, Amin"'
Autor:
Sun, Keqiang, Jourabloo, Amin, Bhalodia, Riddhish, Meshry, Moustafa, Rong, Yu, Yang, Zhengyu, Nguyen-Phuoc, Thu, Haene, Christian, Xu, Jiu, Johnson, Sam, Li, Hongsheng, Bouaziz, Sofien
Photo-realistic and controllable 3D avatars are crucial for various applications such as virtual and mixed reality (VR/MR), telepresence, gaming, and film production. Traditional methods for avatar creation often involve time-consuming scanning and r
Externí odkaz:
http://arxiv.org/abs/2408.13674
Autor:
Jourabloo, Amin, Gecer, Baris, De la Torre, Fernando, Saragih, Jason, Wei, Shih-En, Wang, Te-Li, Lombardi, Stephen, Belko, Danielle, Trimble, Autumn, Badino, Hernan
Social presence, the feeling of being there with a real person, will fuel the next generation of communication systems driven by digital humans in virtual reality (VR). The best 3D video-realistic VR avatars that minimize the uncanny effect rely on p
Externí odkaz:
http://arxiv.org/abs/2104.04794
Using printed photograph and replaying videos of biometric modalities, such as iris, fingerprint and face, are common attacks to fool the recognition systems for granting access as the genuine user. With the growing online person-to-person shopping (
Externí odkaz:
http://arxiv.org/abs/2003.13043
Face anti-spoofing is designed to keep face recognition systems from recognizing fake faces as the genuine users. While advanced face anti-spoofing methods are developed, new types of spoof attacks are also being created and becoming a threat to all
Externí odkaz:
http://arxiv.org/abs/1904.02860
Many prior face anti-spoofing works develop discriminative models for recognizing the subtle differences between live and spoof faces. Those approaches often regard the image as an indivisible unit, and process it holistically, without explicit model
Externí odkaz:
http://arxiv.org/abs/1807.09968
Face anti-spoofing is the crucial step to prevent face recognition systems from a security breach. Previous deep learning approaches formulate face anti-spoofing as a binary classification problem. Many of them struggle to grasp adequate spoofing cue
Externí odkaz:
http://arxiv.org/abs/1803.11097
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics, Volume: 24, Issue: 1 (2018)
Convolutional Neural Networks (CNNs) currently achieve state-of-the-art accuracy in image classification. With a growing number of classes, the accuracy usually drops as the possibilities of confusion increase. Interestingly, the class confusion patt
Externí odkaz:
http://arxiv.org/abs/1710.06501
Face alignment is a classic problem in the computer vision field. Previous works mostly focus on sparse alignment with a limited number of facial landmark points, i.e., facial landmark detection. In this paper, for the first time, we aim at providing
Externí odkaz:
http://arxiv.org/abs/1709.01442
Face alignment has witnessed substantial progress in the last decade. One of the recent focuses has been aligning a dense 3D face shape to face images with large head poses. The dominant technology used is based on the cascade of regressors, e.g., CN
Externí odkaz:
http://arxiv.org/abs/1707.06286
Autor:
Jourabloo, Amin, Liu, Xiaoming
Face alignment aims to estimate the locations of a set of landmarks for a given image. This problem has received much attention as evidenced by the recent advancement in both the methodology and performance. However, most of the existing works neithe
Externí odkaz:
http://arxiv.org/abs/1506.03799