The conference paper provides a brief introduction into manifolds from a computer vision perspective. Important manifolds for this research field, like symmetric positive definite matrices and affine transformation matrices, are presented. Furthermore, deep learning methods for important applications like motion estimation, affine motion tracking and pose invariant object detection are outlined.
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A comprehensive survey of geometric deep learning
The survey provides a comprehensive overview of deep learning methods for geometric data (point clouds, voxels, network graphs etc.). The relevant knowledge and theoretical background of geometric deep learning is presented first. In the following section, different network models for graph and manifold data are reviewed. Finally, applications of these methods in various fields and… Continue reading A comprehensive survey of geometric deep learning
An introduction to manifolds
This book provides an introduction to the theory of manifolds in an easy readable way. Key concepts of manifolds, angent spaces and Lie group / Lie algebra are presented. Furthermore, it gives an introduction into differential forms, integration and De Rham theory.
From Images to Text New forms of Human-AI Interaction
Recent progress in the Computer Vision and Natural Language Processing communities have made it possible to connect Vision and Language together in a variety of different tasks which lie at the intersection of Vision, Language, and Embodied AI. Those tasks range from generating meaningful descriptions of images, to answering questions and navigating agents in unseen… Continue reading From Images to Text New forms of Human-AI Interaction
Video Summarization Using Deep Neural Networks: A Survey
Video summarization technologies aim to create a concise and complete synopsis by selecting the most informative parts of the video content. Several approaches have been developed over the last couple of decades and the current state of the art is represented by methods that rely on modern deep neural network architectures. This work focuses on… Continue reading Video Summarization Using Deep Neural Networks: A Survey
Machine Listening for Music and Sound Analysis
Lecture material on Machine Listening for Music and Sound Analysis lecture