1 citations · 1 across the 5 of their papers we have counts for
5 papers
Boosting Graph Neural Network Expressivity with Learnable Lanczos Constraints
Niloofar Azizi, Nils Kriege, Horst Bischof
Graph Neural Networks (GNNs) excel in handling graph-structured data but often underperform in link prediction tasks compared to classical methods, mainly due to the limitations of…
Occlusion Handling in 3D Human Pose Estimation with Perturbed Positional Encoding
Niloofar Azizi, Mohsen Fayyaz, Horst Bischof
Understanding human behavior fundamentally relies on accurate 3D human pose estimation. Graph Convolutional Networks (GCNs) have recently shown promising advancements, delivering s…
3D Human Pose Estimation Using Möbius Graph Convolutional Networks
Niloofar Azizi, Horst Possegger, Emanuele Rodolà +1
3D human pose estimation is fundamental to understanding human behavior. Recently, promising results have been achieved by graph convolutional networks (GCNs), which achieve state-…
Complex Valued Gated Auto-encoder for Video Frame Prediction
Niloofar Azizi, Nils Wandel, Sven Behnke
In recent years, complex valued artificial neural networks have gained increasing interest as they allow neural networks to learn richer representations while potentially incorpora…
Location Dependency in Video Prediction
Niloofar Azizi, Hafez Farazi, Sven Behnke
Deep convolutional neural networks are used to address many computer vision problems, including video prediction. The task of video prediction requires analyzing the video frames,…