Search Results

Motivated by the Parameter-Efficient Fine-Tuning (PEFT) in large language models, we propose LoRAT, a method that unveils the power of larger Vision Transformers (ViT) for tracking within laboratory-level resources. The essence of our work lies in ...

Recently, Transformer based visual object tracking methods have achieved impressive advancements and significantly improved tracking performance. Transformer includes two modules of self-attention and cross-attention for those methods. However, it ...

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 ...

The improvement of the metaheuristic algorithms is one of the exciting topics to investigators in current years to resolve the optimisation and engineering problems. One of the population-based search methods, i.e., moth-flame optimisation algorithm (MFO),...

There has been an increasing emphasis on building large-scale datasets as the driver of deep learning-based trackers' success. However, accurately annotating tracking data is highly labor-intensive and expensive, making it infeasible in real-world ...

Player tracking in broadcast soccer videos has received widespread attention in the field of sports video analysis, however, we note that there is not a suitable tracking algorithm specifically for soccer video, and the existing benchmarks used for ...

Interaction through dynamic hand gestures is an interesting yet challenging area because in computer vision the hand is a non-rigid object that moves unpredictably. Additionally, the real-time backgrounds are unstable. RGB data of moving hand are ...

Motion prediction obtains pedestrian moving direction, which is fundamental control parameters for robot tail following. In this paper, a tracker named ADNet-PMP is proposed for pedestrian motion prediction. The ADNet model is improved with interlace ...

Recently, Siamese networks based tracking algorithms have shown favorable performance. Latest work focuses on better feature embedding and target state estimation, which greatly improves the accuracy. Nevertheless, the simple cross-correlation operation ...

We developed a system for visualizing golf putting trajectories that can be used in live broadcasting. The trajectory computer graphics (CGs) in a golf putting scene are useful for visualizing the results of past plays and the shape of the green. In ...

Visual tracking has recently gained a great advance with the use of the convolutional neural network (CNN). Usually, existing CNN‐based trackers exploit the features from a single layer or a certain combination of multiple layers. However, these features ...

This paper tackles the task of online video object segmentation with weak supervision, i.e., labeling the target object and background with pixel-level accuracy in unconstrained videos, given only one bounding box information in the first frame. We ...

This paper describes a system for visualizing sword trajectories in fencing. Fencing swords are very thin and move so fast that it is difficult for audiences to follow their movements even in slow-motion video replays. The system thus tracks the tips of ...

Modern driver assistance systems enable a variety of use cases which rely on accurate localization information of all traffic participants. Due to the unavailability of satellite-based localization, the use of infrastructure cameras is a promising ...

We developed a system for visualizing stone trajectories in curling games for live broadcasts. Robustly tracking a moving stone from curling video sequences is difficult because the stone is frequently hidden by the brushes held by the players and the ...

ResNet with hundreds or even thousands of layers has become the most successful image recognition model in the computer vision community. However, we do not know whether this deeper architecture has better transferability than the traditional models. In ...

Visual object tracking is a challenging task because designing an effective and efficient appearance model is difficult. Current online tracking algorithms treat tracking as a classification task and use labelled samples to update appearance model. ...

Visual object tracking (VOT) is an important subfield of computer vision. It has widespread application domains, and has been considered as an important part of surveillance and security system. VOA facilitates finding the position of target in image ...

A challenging problem that needs to be faced in visual object tracking is occlusion, which includes partial occlusion, complete occlusion and blur. Some tracking methods use motion models to predict the location of the occluded objects, and others use ...

Elongated objects have various shapes and can shift, rotate, change scale, and be rigid or deform by flexing, articulating, and vibrating, with examples as varied as a glass bottle, a robotic arm, a surgical suture, a finger pair, a tram, and a guitar ...