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Found 6 papers, 1 papers with code
Transcending conventional biometry frontiers: Diffusive Dynamics PPG Biometry
In the first half of the 20th century, a first pulse oximeter was available to measure blood flow changes in the peripheral vascular net.
Towards Dense People Detection with Deep Learning and Depth images
This paper proposes a DNN-based system that detects multiple people from a single depth image.
Exploiting the ConvLSTM: Human Action Recognition using Raw Depth Video-Based Recurrent Neural Networks
As in many other different fields, deep learning has become the main approach in most computer vision applications, such as scene understanding, object recognition, computer-human interaction or human action recognition (HAR).
3DFCNN: Real-Time Action Recognition using 3D Deep Neural Networks with Raw Depth Information
Human actions recognition is a fundamental task in artificial vision, that has earned a great importance in recent years due to its multiple applications in different areas.
DPDnet: A Robust People Detector using Deep Learning with an Overhead Depth Camera
In this paper we propose a method based on deep learning that detects multiple people from a single overhead depth image with high reliability.
Deep Shape-from-Template: Wide-Baseline, Dense and Fast Registration and Deformable Reconstruction from a Single Image
Compared to previous non-DNN SfT methods, it does not involve numerical optimization at run-time, and is a dense, wide-baseline solution that does not demand, and does not suffer from, feature-based matching.
