Figure 5: Examples of upsampling an image (top row) by a factor of 8 and a zoom-in on the bottom left of the image (bottom row), showing: (a) HR color, (b) LR ARKit depth map, (c) HR ground truth and …
We introduce ARKit LabelMaker, a large-scale real-world 3D dataset with dense semantic an-notation that is more than three times larger than prior largest dataset.
In this work, we use Apple’s ARKit to predict 3D locations of hand joints for a headset-based application. We set up a collaborative AR experience with an iPhone and an iPad using Multipeer Connectivity to …
Similar to the image detection demonstrated, it’s possible to use ARKit to detect 3D objects in the real world based off reference models. Unlike 2D images, these cannot (currently?) be tracked
ARKit features Tracking: Uses visual odometer, data from camera and motion sensor which enables placing of objects
Adoption rate of this framework has been huge since its inception with more than 13 million AR applications built using this framework within the first six months of its release. The graph shows …
In this thesis we measure the accuracy of the VIO algorithm of ARKit, an AR framework by Apple. An application was developed to allow for the placement of a bounding box onto an object and recording …