Prepended Domain Transformer: Heterogeneous Face Recognition without Bells and Whistles

2 code implementations • 12 Oct 2022 • Anjith George, Amir Mohammadi, Sebastien Marcel

The core idea of the proposed approach is to add a novel neural network block called Prepended Domain Transformer (PDT) in front of a pre-trained face recognition (FR) model to address the domain gap.

Contrastive Learning Face Recognition +1

Iris Liveness Detection Competition (LivDet-Iris) -- The 2020 Edition

no code implementations • 1 Sep 2020 • Priyanka Das, Joseph McGrath, Zhaoyuan Fang, Aidan Boyd, Ganghee Jang, Amir Mohammadi, Sandip Purnapatra, David Yambay, Sébastien Marcel, Mateusz Trokielewicz, Piotr Maciejewicz, Kevin Bowyer, Adam Czajka, Stephanie Schuckers, Juan Tapia, Sebastian Gonzalez, Meiling Fang, Naser Damer, Fadi Boutros, Arjan Kuijper, Renu Sharma, Cunjian Chen, Arun Ross

Launched in 2013, LivDet-Iris is an international competition series open to academia and industry with the aim to assess and report advances in iris Presentation Attack Detection (PAD).

Benchmarking

PCB Defect Detection Using Denoising Convolutional Autoencoders

no code implementations • 28 Aug 2020 • Saeed Khalilian, Yeganeh Hallaj, Arian Balouchestani, Hossein Karshenas, Amir Mohammadi

We trained our model with defective PCBs and forced it to repair the defective parts.

Defect Detection Denoising

Smartphone Multi-modal Biometric Authentication: Database and Evaluation

no code implementations • 5 Dec 2019 • Raghavendra Ramachandra, Martin Stokkenes, Amir Mohammadi, Sushma Venkatesh, Kiran Raja, Pankaj Wasnik, Eric Poiret, Sébastien Marcel, Christoph Busch

One of the unique features of this dataset is that it is collected in four different geographic locations representing a diverse population and ethnicity.