most citedLoss Function Search for Face Recognition

29 citations · 60 across the 5 of their papers we have counts for

collaborators

5 papers

eess.AS20203 cited

Weakly Supervised Construction of ASR Systems with Massive Video Data

Mengli Cheng, Chengyu Wang, Xu Hu +2

Building Automatic Speech Recognition (ASR) systems from scratch is significantly challenging, mostly due to the time-consuming and financially-expensive process of annotating a la…

cs.CV202029 cited

Loss Function Search for Face Recognition

Xiaobo Wang, Shuo Wang, Cheng Chi +2

In face recognition, designing margin-based (e.g., angular, additive, additive angular margins) softmax loss functions plays an important role in learning discriminative features.…

cs.CV201913 cited

Mis-classified Vector Guided Softmax Loss for Face Recognition

Xiaobo Wang, Shifeng Zhang, Shuo Wang +3

Face recognition has witnessed significant progress due to the advances of deep convolutional neural networks (CNNs), the central task of which is how to improve the feature discri…

cs.CV201910 cited

A High-Efficiency Framework for Constructing Large-Scale Face Parsing Benchmark

Yinglu Liu, Hailin Shi, Yue Si +3

Face parsing, which is to assign a semantic label to each pixel in face images, has recently attracted increasing interest due to its huge application potentials. Although many fac…

cs.CV20195 cited

Grand Challenge of 106-Point Facial Landmark Localization

Yinglu Liu, Hao Shen, Yue Si +18

Facial landmark localization is a very crucial step in numerous face related applications, such as face recognition, facial pose estimation, face image synthesis, etc. However, pre…