no code implementations • ICCV 2023 • Yuchen Liu, Yabo Chen, Mengran Gou, Chun-Ting Huang, Yaoming Wang, Wenrui Dai, Hongkai Xiong
In this paper, we propose the first Unsupervised Domain Generalization framework for Face Anti-Spoofing, namely UDG-FAS, which could exploit large amounts of easily accessible unlabeled data to learn generalizable features for enhancing the low-data regime of FAS.
no code implementations • CVPR 2018 • Mengran Gou, Fei Xiong, Octavia Camps, Mario Sznaier
In addition, we propose a novel sub-matrix square-root layer, which can be used to normalize the output of the convolution layer directly and mitigate the dimensionality problem with off-the-shelf compact pooling methods.
no code implementations • CVPR 2016 • Xikang Zhang, Yin Wang, Mengran Gou, Mario Sznaier, Octavia Camps
In this paper we propose a new framework to compare and classify temporal sequences.
3 code implementations • 31 May 2016 • Srikrishna Karanam, Mengran Gou, Ziyan Wu, Angels Rates-Borras, Octavia Camps, Richard J. Radke
To ensure a fair comparison, all of the approaches were implemented using a unified code library that includes 11 feature extraction algorithms and 22 metric learning and ranking techniques.
no code implementations • 1 Apr 2016 • Mengran Gou, Xikang Zhang, Angels Rates-Borras, Sadjad Asghari-Esfeden, Mario Sznaier, Octavia Camps
Our experiments on the original and the appearance impaired datasets demonstrate the benefits of incorporating dynamics-based information with appearance-based information to re-identification algorithms.