相关论文: Context-Responsive Labeling in Augmented Reality
Real-world datasets collected with sensor networks often contain incomplete and uncertain labels as well as artefacts arising from the system environment. Complete and reliable labeling is often infeasible for large-scale and long-term…
Augmented Reality (AR) smartglasses are increasingly regarded as the next generation personal computing platform. However, there is a lack of understanding about how to design communication systems using them. We present ARcall, a novel…
Road detection or traversability analysis has been a key technique for a mobile robot to traverse complex off-road scenes. The problem has been mainly formulated in early works as a binary classification one, e.g. associating pixels with…
For humans, understanding the relationships between objects using visual signals is intuitive. For artificial intelligence, however, this task remains challenging. Researchers have made significant progress studying semantic relationship…
Augmented Virtuality integrates physical content into virtual environments, but the occlusion of physical by virtual content is a challenge. This unwanted occlusion may disrupt user interactions with physical devices and compromise safety…
Augmented Reality (AR) systems, while enhancing task performance through real-time guidance, pose risks of inducing cognitive tunneling-a hyperfocus on virtual content that compromises situational awareness (SA) in safety-critical…
The image annotation stage is a critical and often the most time-consuming part required for training and evaluating object detection and semantic segmentation models. Deployment of the existing models in novel environments often requires…
Despite impressive advancements in Autonomous Driving Systems (ADS), navigation in complex road conditions remains a challenging problem. There is considerable evidence that evaluating the subjective risk level of various decisions can…
A challenge of the computer vision community is to understand the semantics of an image, in order to allow image reconstruction based on existing high-level features or to better analyze (semi-)labelled datasets. Towards addressing this…
Most meta-learning methods assume that the (very small) context set used to establish a new task at test time is passively provided. In some settings, however, it is feasible to actively select which points to label; the potential gain from…
Recent advancements in AI and edge computing have accelerated the development of machine-centric applications (MCAs), such as smart surveillance systems. In these applications, video cameras and sensors offload inference tasks like license…
Despite the remarkable performance of supervised medical image segmentation models, relying on a large amount of labeled data is impractical in real-world situations. Semi-supervised learning approaches aim to alleviate this challenge using…
Augmented reality devices have the potential to enhance human perception and enable other assistive functionalities in complex conversational environments. Effectively capturing the audio-visual context necessary for understanding these…
Surgical navigation provides real-time guidance by estimating the pose of patient anatomy and surgical instruments to visualize relevant intraoperative information. In conventional systems, instruments are typically tracked using fiducial…
Most image-text retrieval work adopts binary labels indicating whether a pair of image and text matches or not. Such a binary indicator covers only a limited subset of image-text semantic relations, which is insufficient to represent…
Semantic correspondence is the problem of establishing correspondences across images depicting different instances of the same object or scene class. One of recent approaches to this problem is to estimate parameters of a global…
Advancements in augmented reality (AR) technologies offer immense potential for mobile experiences. However, most commercial and educational AR systems assume a baseline of predictable user behavior and stationary interaction. Preschoolers…
Current tablet-based interfaces for drone operations often impose a heavy cognitive load on pilots and reduce situational awareness by dividing attention between the video feed and the real world. To address these challenges, we designed a…
Document layout analysis is a key area in document research, involving techniques like text mining and visual analysis. Despite various methods developed to tackle layout analysis, a critical but frequently overlooked problem is the…
Great labels make great models. However, traditional labeling approaches for tasks like object detection have substantial costs at scale. Furthermore, alternatives to fully-supervised object detection either lose functionality or require…