Currently, multimedia systems and computer vision algorithms are increasingly playing a crucial role in biological research. However, due to the significant difference between macro and micro scenarios, it is impractical to directly transfer existing ...

Interacting with real-world objects is one of the fundamental tasks in multimedia. Despite its importance, existing object pose estimation targets only rigid objects. This demonstration proposes a novel application for non-rigid object pose estimation. ...

We present H2V4Sports, a real-time horizontal-to-vertical video converter specifically designed for sports live broadcasts. With the increasing demand of smartphone users who prefer to watch sports events on their vertical screens anywhere, anytime, our ...

RGB and thermal infrared (TIR) data have different visual properties, which make their fusion essential for effective object tracking in diverse environments and scenes. Existing RGBT tracking methods commonly use attention mechanisms to generate ...

Nighttime tracking is challenging due to the lack of sufficient training data and scene diversity. Unsupervised domain adaptation is a solution by transferring knowledge from day (source domain) to night (target domain). It typically involves adversarial ...

Siamese tracking exploits the template and the search region features to adaptively locate arbitrary objects in the tracking. A noteworthy issue is that both foreground and background mix in the template, and thus a tracker needs to learn what the target ...

Over the past years, augmented reality (AR) based on mobile phones has gained great attention. When multiple phones are used in AR applications, collaborative simultaneous localization and mapping (SLAM) is considered one of the enabling technologies, ...

Convolutional Neural Networks (CNNs) are vulnerable to adversarial attacks in which visually imperceptible perturbations can deceive CNN-based models. While current research on adversarial attacks in single object tracking exists, it overlooks a critical ...

Multiple object tracking (MOT) has been successfully investigated in computer vision. However, MOT for the videos captured by unmanned aerial vehicles (UAV) is still challenging due to small object size, blurred object appearance, and very large and/or ...

Current mainstream vision-language (VL) tracking framework consists of three parts,i.e., a visual feature extractor, a language feature extractor, and a fusion model. To pursue better performance, a natural modus operandi for VL tracking is employing ...

Multiple object tracking (MOT) tends to become more challenging when severe occlusions occur. In this paper, we analyze the limitations of traditional Convolutional Neural Network-based methods and Transformer-based methods in handling occlusions and ...

Open-World Tracking (OWT) presents a challenging yet emerging problem, aiming to track every object of any category. Different from traditional Multi-Object Tracking (MOT), OWT needs to additionally track targets beyond predefined categories in the ...