Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge in the Era of Synthetic Data

2 code implementations • 16 Apr 2024 • Ivan DeAndres-Tame, Ruben Tolosana, Pietro Melzi, Ruben Vera-Rodriguez, Minchul Kim, Christian Rathgeb, Xiaoming Liu, Aythami Morales, Julian Fierrez, Javier Ortega-Garcia, Zhizhou Zhong, Yuge Huang, Yuxi Mi, Shouhong Ding, Shuigeng Zhou, Shuai He, Lingzhi Fu, Heng Cong, Rongyu Zhang, Zhihong Xiao, Evgeny Smirnov, Anton Pimenov, Aleksei Grigorev, Denis Timoshenko, Kaleb Mesfin Asfaw, Cheng Yaw Low, Hao liu, Chuyi Wang, Qing Zuo, Zhixiang He, Hatef Otroshi Shahreza, Anjith George, Alexander Unnervik, Parsa Rahimi, Sébastien Marcel, Pedro C. Neto, Marco Huber, Jan Niklas Kolf, Naser Damer, Fadi Boutros, Jaime S. Cardoso, Ana F. Sequeira, Andrea Atzori, Gianni Fenu, Mirko Marras, Vitomir Štruc, Jiang Yu, Zhangjie Li, Jichun Li, Weisong Zhao, Zhen Lei, Xiangyu Zhu, Xiao-Yu Zhang, Bernardo Biesseck, Pedro Vidal, Luiz Coelho, Roger Granada, David Menotti

Synthetic data is gaining increasing relevance for training machine learning models.

Benchmarking Face Recognition

FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data

1 code implementation • 17 Nov 2023 • Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez, Minchul Kim, Christian Rathgeb, Xiaoming Liu, Ivan DeAndres-Tame, Aythami Morales, Julian Fierrez, Javier Ortega-Garcia, Weisong Zhao, Xiangyu Zhu, Zheyu Yan, Xiao-Yu Zhang, Jinlin Wu, Zhen Lei, Suvidha Tripathi, Mahak Kothari, Md Haider Zama, Debayan Deb, Bernardo Biesseck, Pedro Vidal, Roger Granada, Guilherme Fickel, Gustavo Führ, David Menotti, Alexander Unnervik, Anjith George, Christophe Ecabert, Hatef Otroshi Shahreza, Parsa Rahimi, Sébastien Marcel, Ioannis Sarridis, Christos Koutlis, Georgia Baltsou, Symeon Papadopoulos, Christos Diou, Nicolò Di Domenico, Guido Borghi, Lorenzo Pellegrini, Enrique Mas-Candela, Ángela Sánchez-Pérez, Andrea Atzori, Fadi Boutros, Naser Damer, Gianni Fenu, Mirko Marras

Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must be covered in more detail.

Face Recognition

Cross Architecture Distillation for Face Recognition

no code implementations • 26 Jun 2023 • Weisong Zhao, Xiangyu Zhu, Zhixiang He, Xiao-Yu Zhang, Zhen Lei

Transformers have emerged as the superior choice for face recognition tasks, but their insufficient platform acceleration hinders their application on mobile devices.

Face Recognition Knowledge Distillation

Grouped Knowledge Distillation for Deep Face Recognition

no code implementations • 10 Apr 2023 • Weisong Zhao, Xiangyu Zhu, Kaiwen Guo, Xiao-Yu Zhang, Zhen Lei

Therefore, we seek to probe the target logits to extract the primary knowledge related to face identity, and discard the others, to make the distillation more achievable for the student network.

Face Recognition Knowledge Distillation

Faster super-resolution imaging with auto-correlation two-step deconvolution

2 code implementations • 19 Sep 2018 • Weisong Zhao, Jian Liu, Chenqi Kong, Yixuan Zhao, Changliang Guo, Chen-Guang Liu, Xiangyan Ding, Xumin Ding, Jiubin Tan, Haoyu Li

Despite super-resolution fluorescence blinking microscopes break the diffraction limit, the intense phototoxic illumination and long-term image sequences thus far still pose to major challenges in visualizing live-organisms.

Optics

Modeling Based on Elman Wavelet Neural Network for Class-D Power Amplifiers

no code implementations • 12 Sep 2013 • Li Wang, Jie Shao, Yaqin Zhong, Weisong Zhao, Reza Malekian

In Class-D Power Amplifiers (CDPAs), the power supply noise can intermodulate with the input signal, manifesting into power-supply induced intermodulation distortion (PS-IMD) and due to the memory effects of the system, there exist asymmetries in the PS-IMDs.