Learning to filter: Siamese relation network for robust tracking
Despite the great success of Siamese-based trackers, their performance under complicated
scenarios is still not satisfying, especially when there are distractors. To this end, we …
scenarios is still not satisfying, especially when there are distractors. To this end, we …
Recent advances in embedding methods for multi-object tracking: a survey
Multi-object tracking (MOT) aims to associate target objects across video frames in order to
obtain entire moving trajectories. With the advancement of deep neural networks and the …
obtain entire moving trajectories. With the advancement of deep neural networks and the …
Multiple object tracking in robotic applications: Trends and challenges
The recent advancement in autonomous robotics is directed toward designing a reliable
system that can detect and track multiple objects in the surrounding environment for …
system that can detect and track multiple objects in the surrounding environment for …
The unmanned aerial vehicle benchmark: Object detection, tracking and baseline
With the increasing popularity of Unmanned Aerial Vehicles (UAVs) in computer vision-
related applications, intelligent UAV video analysis has recently attracted the attention of an …
related applications, intelligent UAV video analysis has recently attracted the attention of an …
Robust multi-drone multi-target tracking to resolve target occlusion: A benchmark
Multi-drone multi-target tracking aims at collabo-ratively detecting and tracking targets
across multiple drones and associating the identities of objects from different drones, which …
across multiple drones and associating the identities of objects from different drones, which …
MS-Faster R-CNN: Multi-stream backbone for improved Faster R-CNN object detection and aerial tracking from UAV images
Tracking objects across multiple video frames is a challenging task due to several difficult
issues such as occlusions, background clutter, lighting as well as object and camera view …
issues such as occlusions, background clutter, lighting as well as object and camera view …
Learning video moment retrieval without a single annotated video
Video moment retrieval has progressed significantly over the past few years, aiming to
search the moment that is most relevant to a given natural language query. Most existing …
search the moment that is most relevant to a given natural language query. Most existing …
Fine-grained spatial alignment model for person re-identification with focal triplet loss
Recent advances of person re-identification have well advocated the usage of human body
cues to boost performance. However, most existing methods still retain on exploiting a …
cues to boost performance. However, most existing methods still retain on exploiting a …
Remote sensing object tracking with deep reinforcement learning under occlusion
Object tracking is an important research direction of space Earth observation in the field of
remote sensing. Although the existing correlation filter-based and deep learning (DL)-based …
remote sensing. Although the existing correlation filter-based and deep learning (DL)-based …
Multi-level cooperative fusion of GM-PHD filters for online multiple human tracking
In this paper, we propose a multi-level cooperative fusion approach to address the online
multiple human tracking problem in a Gaussian mixture probability hypothesis density (GM …
multiple human tracking problem in a Gaussian mixture probability hypothesis density (GM …