Augmented reality (AR) has proven to be an invaluable interactive medium to reduce
cognitive load by bridging the gap between the task-at-hand and relevant information by …

Contactless fingerprint identification systems have been introduced to address the
deficiencies of contact-based fingerprint systems. A number of studies have been reported …

The last decade witnessed increasingly rapid progress in self‐driving vehicle technology,
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …

We introduce GNeRF, a framework to marry Generative Adversarial Networks (GAN) with
Neural Radiance Field (NeRF) reconstruction for the complex scenarios with unknown and …

Visual localization is the task of accurate camera pose estimation in a known scene. It is a
key problem in computer vision and robotics, with applications including self-driving cars …

We present L3-Net-a novel learning-based LiDAR localization system that achieves
centimeter-level localization accuracy, comparable to prior state-of-the-art systems with …

Localization is an indispensable component of a robot's autonomy stack that enables it to
determine where it is in the environment, essentially making it a precursor for any action …

Semantic understanding and localization are fundamental enablers of robot autonomy that
have been tackled as disjoint problems for the most part. While deep learning has enabled …

Absolute camera pose regression methods estimate the position and orientation of a camera
by only using the captured image. A convolutional backbone with a multi-layer perceptron …

Deep learning based localization and mapping has recently attracted significant attention.
Instead of creating hand-designed algorithms through exploitation of physical models or …