35 citations · 57 across the 11 of their papers we have counts for
12 papers
Refining activation downsampling with SoftPool
Alexandros Stergiou, Ronald Poppe, Grigorios Kalliatakis
Convolutional Neural Networks (CNNs) use pooling to decrease the size of activation maps. This process is crucial to increase the receptive fields and to reduce computational requi…
Class Feature Pyramids for Video Explanation
Alexandros Stergiou, Georgios Kapidis, Grigorios Kalliatakis +3
Deep convolutional networks are widely used in video action recognition. 3D convolutions are one prominent approach to deal with the additional time dimension. While 3D convolution…
DisplaceNet: Recognising Displaced People from Images by Exploiting Dominance Level
Grigorios Kalliatakis, Shoaib Ehsan, Maria Fasli +1
Every year millions of men, women and children are forced to leave their homes and seek refuge from wars, human rights violations, persecution, and natural disasters. The number of…
GET-AID: Visual Recognition of Human Rights Abuses via Global Emotional Traits
Grigorios Kalliatakis, Shoaib Ehsan, Maria Fasli +1
In the era of social media and big data, the use of visual evidence to document conflict and human rights abuse has become an important element for human rights organizations and a…
Saliency Tubes: Visual Explanations for Spatio-Temporal Convolutions
Alexandros Stergiou, Georgios Kapidis, Grigorios Kalliatakis +3
Deep learning approaches have been established as the main methodology for video classification and recognition. Recently, 3-dimensional convolutions have been used to achieve stat…
MAT-CNN-SOPC: Motionless Analysis of Traffic Using Convolutional Neural Networks on System-On-a-Programmable-Chip
Somdip Dey, Grigorios Kalliatakis, Sangeet Saha +3
Intelligent Transportation Systems (ITS) have become an important pillar in modern "smart city" framework which demands intelligent involvement of machines. Traffic load recognitio…
Exploring object-centric and scene-centric CNN features and their complementarity for human rights violations recognition in images
Grigorios Kalliatakis, Shoaib Ehsan, Ales Leonardis +1
Identifying potential abuses of human rights through imagery is a novel and challenging task in the field of computer vision, that will enable to expose human rights violations ove…
Material Classification in the Wild: Do Synthesized Training Data Generalise Better than Real-World Training Data?
Grigorios Kalliatakis, Anca Sticlaru, George Stamatiadis +4
We question the dominant role of real-world training images in the field of material classification by investigating whether synthesized data can generalise more effectively than r…
A Paradigm Shift: Detecting Human Rights Violations Through Web Images
Grigorios Kalliatakis, Shoaib Ehsan, Klaus D. McDonald-Maier
The growing presence of devices carrying digital cameras, such as mobile phones and tablets, combined with ever improving internet networks have enabled ordinary citizens, victims…
Detection of Human Rights Violations in Images: Can Convolutional Neural Networks help?
Grigorios Kalliatakis, Shoaib Ehsan, Maria Fasli +3
After setting the performance benchmarks for image, video, speech and audio processing, deep convolutional networks have been core to the greatest advances in image recognition tas…
Evaluating Deep Convolutional Neural Networks for Material Classification
Grigorios Kalliatakis, Georgios Stamatiadis, Shoaib Ehsan +4
Determining the material category of a surface from an image is a demanding task in perception that is drawing increasing attention. Following the recent remarkable results achieve…
Web-based visualisation of head pose and facial expressions changes: monitoring human activity using depth data
Grigorios Kalliatakis, Nikolaos Vidakis, Georgios Triantafyllidis
Despite significant recent advances in the field of head pose estimation and facial expression recognition, raising the cognitive level when analysing human activity presents serio…