Artificial intelligence (AI) in augmented reality (AR)-assisted manufacturing applications: a review
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 …
cognitive load by bridging the gap between the task-at-hand and relevant information by …
Neural network-based recent research developments in SLAM for autonomous ground vehicles: A review
The development of autonomous vehicles has prompted an interest in exploring various
techniques in navigation. One such technique is simultaneous localization and mapping …
techniques in navigation. One such technique is simultaneous localization and mapping …
Omni3d: A large benchmark and model for 3d object detection in the wild
Recognizing scenes and objects in 3D from a single image is a longstanding goal of
computer vision with applications in robotics and AR/VR. For 2D recognition, large datasets …
computer vision with applications in robotics and AR/VR. For 2D recognition, large datasets …
Transformers in self-supervised monocular depth estimation with unknown camera intrinsics
The advent of autonomous driving and advanced driver assistance systems necessitates
continuous developments in computer vision for 3D scene understanding. Self-supervised …
continuous developments in computer vision for 3D scene understanding. Self-supervised …
Learning monocular visual odometry via self-supervised long-term modeling
Monocular visual odometry (VO) suffers severely from error accumulation during frame-to-
frame pose estimation. In this paper, we present a self-supervised learning method for VO …
frame pose estimation. In this paper, we present a self-supervised learning method for VO …
Unsupervised action segmentation by joint representation learning and online clustering
We present a novel approach for unsupervised activity segmentation which uses video
frame clustering as a pretext task and simultaneously performs representation learning and …
frame clustering as a pretext task and simultaneously performs representation learning and …
Deep geometry-aware camera self-calibration from video
Accurate intrinsic calibration is essential for camera-based 3D perception, yet, it typically
requires targets of well-known geometry. Here, we propose a camera self-calibration …
requires targets of well-known geometry. Here, we propose a camera self-calibration …
Pseudo rgb-d for self-improving monocular slam and depth prediction
Abstract Classical monocular Simultaneous Localization And Mapping (SLAM) and the
recently emerging convolutional neural networks (CNNs) for monocular depth prediction …
recently emerging convolutional neural networks (CNNs) for monocular depth prediction …
Deep learning for camera calibration and beyond: A survey
Camera calibration involves estimating camera parameters to infer geometric features from
captured sequences, which is crucial for computer vision and robotics. However …
captured sequences, which is crucial for computer vision and robotics. However …
LSTM and filter based comparison analysis for indoor global localization in UAVs
Deep learning (DL) based localization and Simultaneous Localization and Mapping (SLAM)
has recently gained considerable attention demonstrating remarkable results. Instead of …
has recently gained considerable attention demonstrating remarkable results. Instead of …