Papers

Week 1

Title	Link	Comments after the first read/glance	Worthy?
Generative One-Shot Face Recognition	https://arxiv.org/pdf/1910.04860.pdf	A mix of GANs and one-shot techniques to get better accuracy on face recog.	YES
Data-specific Adaptive Threshold for Face Recognition and Authentication	https://arxiv.org/pdf/1810.11160v1.pdf	Good Approach for the threshold selection. But unsure if helpful for oneshot.	YES
Siamese Neural Networks for One-shot Image Recognition	https://www.cs.cmu.edu/~rsalakhu/papers /oneshot1.pdf	Discusss the siamese network for character recog in detail. This is the idea behind face recog. But isnt worth looking into for our project's goals.	NO
FaceNet: A Unified Embedding for Face Recognition and Clustering	https://arxiv.org/pdf/1503.03832v3.pdf	The SOTA face recog model for now in the world. Used Triplet Loss function for training	YES
Deep Polynomial Neural Networks	https://arxiv.org/pdf/2006.13026v2.pdf	Nice paper which discusses the use of only linear activation functions to learn patterns. But is not very relevant (it is an all new approach which we can try after trying traditional non-linear act. functions first) to the problem at hand (FR)	NO
SphereFace: Deep Hypersphere Embedding for Face Recognition	https://arxiv.org/pdf/1704.08063.pdf	Awesome paper which discusses a radical and awesome new method to train FR systems.	YES

Survey Paper on Face Recognition Model Papers : https://arxiv.org/pdf/1804.06655.pdf

Useful Blogpost : https://machinelearningmastery.com/one-shot-learning-with-siamese-networks-contrastive-and-triplet-loss-for-face-recognition/

Video on ArcFace : https://www.youtube.com/watch?v=H1qEp_czI1I&ab_channel=platformai

Papers To Read

• VGGFace2 : https://arxiv.org/pdf/1710.08092.pdf

• NormFace : https://arxiv.org/abs/1704.06369

• ArcFace : https://arxiv.org/pdf/1801.07698.pdf