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Found 7 papers, 1 papers with code
NToP: NeRF-Powered Large-scale Dataset Generation for 2D and 3D Human Pose Estimation in Top-View Fisheye Images
Through this pipeline, we create a novel dataset NToP570K (NeRF-powered Top-view human Pose dataset for fisheye cameras with over 570 thousand images), and conduct an extensive evaluation of its efficacy in enhancing neural networks for 2D and 3D top-view human pose estimation.
Human Pose Estimation in Monocular Omnidirectional Top-View Images
In our work we propose a new dataset for training and evaluation of CNNs for the task of keypoint detection in omnidirectional images.
OmniPD: One-Step Person Detection in Top-View Omnidirectional Indoor Scenes
To enhance the fine-tuning process, we add a subset of HDA Person dataset and a subset of PIROPOdatabase and reduce the number of perspective images to PASCAL VOC07.
OmniFlow: Human Omnidirectional Optical Flow
To verify the data for training volumetric correspondence networks for optical flow estimation we train different subsets of the data and test on OmniFlow with and without Test-Time-Augmentation.
Learning from THEODORE: A Synthetic Omnidirectional Top-View Indoor Dataset for Deep Transfer Learning
Recent work about synthetic indoor datasets from perspective views has shown significant improvements of object detection results with Convolutional Neural Networks(CNNs).
Improved Person Detection on Omnidirectional Images with Non-maxima Suppression
For this purpose we fine-tuned the soft non-maximum suppression with Gaussian smoothing.
Cubes3D: Neural Network based Optical Flow in Omnidirectional Image Scenes
We investigate CNN architectures to determine high motion variations caused by the geometry of fish-eye images.
