As the most critical components in a sentence, subject, predicate and ob...
Domain adaptive detection aims to improve the generality of a detector,
...
Multi-object tracking (MOT) is a fundamental problem in computer vision ...
Effective feature fusion of multispectral images plays a crucial role in...
Multimodal vision-language (VL) learning has noticeably pushed the tende...
Recent video inpainting methods have made remarkable progress by utilizi...
The vanilla image completion approaches are sensitive to the large missi...
Current arbitrary style transfer models are limited to either image or v...
Gun violence is a critical security problem, and it is imperative for th...
Planar object tracking is a critical computer vision problem and has dra...
Domain adaptive detection aims to improve the generalization of detector...
Automatic security inspection relying on computer vision technology is a...
Image inpainting seeks a semantically consistent way to recover the corr...
Relying on Transformer for complex visual feature learning, object track...
Multi-animal tracking (MAT), a multi-object tracking (MOT) problem, is
c...
Transformer has recently demonstrated clear potential in improving visua...
Objectives. The aim of this study was to investigate whether a deep
conv...
Crowd counting on the drone platform is an interesting topic in computer...
High quality object proposals are crucial in visual tracking algorithms ...
Visual tracking has achieved considerable progress in recent years. Howe...
Despite great recent advances in visual tracking, its further developmen...
In an augmented reality (AR) application, placing labels in a manner tha...
Generic visual tracking is difficult due to many challenge factors (e.g....
Attribution editing has shown remarking progress by the incorporating of...
Detecting objects in aerial images is challenging for at least two reaso...
Recent progresses in model-free single object tracking (SOT) algorithms ...
Region proposal networks (RPN) have been recently combined with the Siam...
Recurrent neural networks (RNNs) have shown the ability to improve scene...
In this paper, we present LaSOT, a high-quality benchmark for Large-scal...
Spatial misalignment caused by variations in poses and viewpoints is one...
In this paper, we propose a graph correspondence transfer (GCT) approach...
Deep convolutional neural networks (CNNs) have demonstrated dominant
per...
Being intensively studied, visual object tracking has witnessed great
ad...
Recently recurrent neural networks (RNNs) have demonstrated the ability ...
Generative modeling, which learns joint probability distribution from
tr...
Being intensively studied, visual tracking has seen great recent advance...
Convolutional neural network (CNN) has drawn increasing interest in visu...
Context in image is crucial for scene labeling while existing methods on...