Learning monocular depth estimation infusing traditional stereo knowledge
Depth estimation from a single image represents a fascinating, yet challenging problem with
countless applications. Recent works proved that this task could be learned without direct …
countless applications. Recent works proved that this task could be learned without direct …
Deepusps: Deep robust unsupervised saliency prediction via self-supervision
Deep neural network (DNN) based salient object detection in images based on high-quality
labels is expensive. Alternative unsupervised approaches rely on careful selection of …
labels is expensive. Alternative unsupervised approaches rely on careful selection of …
[PDF][PDF] Unsupervised Fine-tuning of Optical Flow for Better Motion Boundary Estimation.
T Alhersh, H Stuckenschmidt - VISIGRAPP (5: VISAPP), 2019 - scitepress.org
Recently, convolutional neural network (CNN) based approaches have proven to be
successful in optical flow estimation in the supervised as well as in the unsupervised training …
successful in optical flow estimation in the supervised as well as in the unsupervised training …
From motion to human activity recognition
T Alhersh - 2021 - madoc.bib.uni-mannheim.de
Advancements in wearable technology have the potential to transform the quality of life,
business, and the global economy. Body sensors can be used in human activity recognition …
business, and the global economy. Body sensors can be used in human activity recognition …