Many activation values of Convolutional Neural Networks (CNNs) are zeros due to ReLU
(Rectified Linear Unit), one of the most common activation functions used in modern neural …

For autonomous driving, it is imperative to perform various high-computation image
recognition tasks with high accuracy, utilizing diverse sensors to perceive the surrounding …

To understand how well a proposed augmented reality (AR) solution works, existing papers
often conducted tailored and isolated evaluations for specific AR tasks, eg, depth or lighting …

Accurate metric depth can help achieve more realistic user interactions such as object
placement and occlusion detection in mobile augmented reality (AR). However, it can be …

High-resolution depth estimation, with a minimum resolution of, is essential for achieving
more immersive experiences in on-device 3D vision applications. However, implementing …

We present a deep neural network‐based method that acquires high‐quality shape and
spatially varying reflectance of 3D objects using smartphone multi‐lens imaging. Our …

Accurately localizing high-speed dynamic objects in 3D space with low latency is crucial for
various robotic applications. Current methods face challenges due to extended exposure …

Firefighters still rely on coarse remote sensing and inaccurate eyewitness reports to localize
spreading wildfires. Despite advances in sensing, UAVs, and computer vision, the …