Visible and infrared image fusion (VIF) has attracted a lot of interest in recent years due to its
application in many tasks, such as object detection, object tracking, scene segmentation …

In this paper, we present a new sequence-to-sequence learning framework for visual
tracking, dubbed SeqTrack. It casts visual tracking as a sequence generation problem …

Visible-modal object tracking gives rise to a series of downstream multi-modal tracking
tributaries. To inherit the powerful representations of the foundation model, a natural modus …

Most current RGB-T trackers adopt a two-stream structure to extract unimodal RGB and
thermal features and complex fusion strategies to achieve multi-modal feature fusion, which …

As a fundamental task in computer vision, visual object tracking has received much attention
in recent years. Most studies focus on short-term visual tracking which addresses shorter …

In the realm of video object tracking auxiliary modalities such as depth thermal or event data
have emerged as valuable assets to complement the RGB trackers. In practice most existing …

Thermal infrared (TIR) target tracking is susceptible to occlusion and similarity interference,
which obviously affects the tracking results. To resolve this problem, we develop an Aligned …

Most existing RGB-based trackers target low frame rate benchmarks of around 30 frames
per second. This setting restricts the tracker's functionality in the real world, especially for fast …

The 3-D object detection with light detection and ranging (LiDAR) point clouds is a
challenging problem, which requires 3-D scene understanding, yet this task is critical to …

Visual object tracking aims to localize the target object of each frame based on its initial
appearance in the first frame. Depending on the input modility tracking tasks can be divided …