26 citations · 73 across the 10 of their papers we have counts for
11 papers
NToP: NeRF-Powered Large-scale Dataset Generation for 2D and 3D Human Pose Estimation in Top-View Fisheye Images
Jingrui Yu, Dipankar Nandi, Roman Seidel +1
Human pose estimation (HPE) in the top-view using fisheye cameras presents a promising and innovative application domain. However, the availability of datasets capturing this viewp…
Applications of Deep Learning for Top-View Omnidirectional Imaging: A Survey
Jingrui Yu, Ana Cecilia Perez Grassi, Gangolf Hirtz
A large field-of-view fisheye camera allows for capturing a large area with minimal numbers of cameras when they are mounted on a high position facing downwards. This top-view omni…
Human Pose Estimation in Monocular Omnidirectional Top-View Images
Jingrui Yu, Tobias Scheck, Roman Seidel +3
Human pose estimation (HPE) with convolutional neural networks (CNNs) for indoor monitoring is one of the major challenges in computer vision. In contrast to HPE in perspective vie…
OmniPD: One-Step Person Detection in Top-View Omnidirectional Indoor Scenes
Jingrui Yu, Roman Seidel, Gangolf Hirtz
We propose a one-step person detector for topview omnidirectional indoor scenes based on convolutional neural networks (CNNs). While state of the art person detectors reach competi…
OmniFlow: Human Omnidirectional Optical Flow
Roman Seidel, André Apitzsch, Gangolf Hirtz
Optical flow is the motion of a pixel between at least two consecutive video frames and can be estimated through an end-to-end trainable convolutional neural network. To this end,…
Unsupervised Domain Adaptation from Synthetic to Real Images for Anchorless Object Detection
Tobias Scheck, Ana Perez Grassi, Gangolf Hirtz
Synthetic images are one of the most promising solutions to avoid high costs associated with generating annotated datasets to train supervised convolutional neural networks (CNN).…
Where to drive: free space detection with one fisheye camera
Tobias Scheck, Adarsh Mallandur, Christian Wiede +1
The development in the field of autonomous driving goes hand in hand with ever new developments in the field of image processing and machine learning methods. In order to fully exp…
A CNN-based Feature Space for Semi-supervised Incremental Learning in Assisted Living Applications
Tobias Scheck, Ana Perez Grassi, Gangolf Hirtz
A Convolutional Neural Network (CNN) is sometimes confronted with objects of changing appearance ( new instances) that exceed its generalization capability. This requires the CNN t…
Learning from THEODORE: A Synthetic Omnidirectional Top-View Indoor Dataset for Deep Transfer Learning
Tobias Scheck, Roman Seidel, Gangolf Hirtz
Recent work about synthetic indoor datasets from perspective views has shown significant improvements of object detection results with Convolutional Neural Networks(CNNs). In this…
Cubes3D: Neural Network based Optical Flow in Omnidirectional Image Scenes
André Apitzsch, Roman Seidel, Gangolf Hirtz
Optical flow estimation with convolutional neural networks (CNNs) has recently solved various tasks of computer vision successfully. In this paper we adapt a state-of-the-art appro…
Improved Person Detection on Omnidirectional Images with Non-maxima Suppression
Roman Seidel, André Apitzsch, Gangolf Hirtz
We propose a person detector on omnidirectional images, an accurate method to generate minimal enclosing rectangles of persons. The basic idea is to adapt the qualitative detection…