59 citations · 154 across the 8 of their papers we have counts for
6 papers · 1 filter
Facial expression and attributes recognition based on multi-task learning of lightweight neural networks
Andrey V. Savchenko
In this paper, the multi-task learning of lightweight convolutional neural networks is studied for face identification and classification of facial attributes (age, gender, ethnici…
Event Recognition with Automatic Album Detection based on Sequential Processing, Neural Attention and Image Captioning
Andrey V. Savchenko
In this paper a new formulation of event recognition task is examined: it is required to predict event categories in a gallery of images, for which albums (groups of photos corresp…
Efficient Facial Representations for Age, Gender and Identity Recognition in Organizing Photo Albums using Multi-output CNN
Andrey V. Savchenko
This paper is focused on the automatic extraction of persons and their attributes (gender, year of born) from album of photos and videos. We propose the two-stage approach, in whic…
Group-level Emotion Recognition using Transfer Learning from Face Identification
Alexandr G. Rassadin, Alexey S. Gruzdev, Andrey V. Savchenko
In this paper, we describe our algorithmic approach, which was used for submissions in the fifth Emotion Recognition in the Wild (EmotiW 2017) group-level emotion recognition sub-c…
Organizing Multimedia Data in Video Surveillance Systems Based on Face Verification with Convolutional Neural Networks
Anastasiia D. Sokolova, Angelina S. Kharchevnikova, Andrey V. Savchenko
In this paper we propose the two-stage approach of organizing information in video surveillance systems. At first, the faces are detected in each frame and a video stream is split…
Probabilistic Neural Network with Complex Exponential Activation Functions in Image Recognition using Deep Learning Framework
Andrey Savchenko
If the training dataset is not very large, image recognition is usually implemented with the transfer learning methods. In these methods the features are extracted using a deep con…