4 papers
An Empirical Study towards Understanding How Deep Convolutional Nets Recognize Falls
Yan Zhang, Heiko Neumann
Detecting unintended falls is essential for ambient intelligence and healthcare of elderly people living alone. In recent years, deep convolutional nets are widely used in human ac…
Local Temporal Bilinear Pooling for Fine-grained Action Parsing
Yan Zhang, Siyu Tang, Krikamol Muandet +2
Fine-grained temporal action parsing is important in many applications, such as daily activity understanding, human motion analysis, surgical robotics and others requiring subtle a…
Classifier-Guided Visual Correction of Noisy Labels for Image Classification Tasks
Alex Bäuerle, Heiko Neumann, Timo Ropinski
Training data plays an essential role in modern applications of machine learning. However, gathering labeled training data is time-consuming. Therefore, labeling is often outsource…
Temporal Human Action Segmentation via Dynamic Clustering
Yan Zhang, He Sun, Siyu Tang +1
We present an effective dynamic clustering algorithm for the task of temporal human action segmentation, which has comprehensive applications such as robotics, motion analysis, and…