This paper addresses the problem of cross-modal object tracking from RGB videos and
event data. Rather than constructing a complex cross-modal fusion network, we explore the …

Different from visible cameras which record intensity images frame by frame, the biologically
inspired event camera produces a stream of asynchronous and sparse events with much …

Recently, some researchers have begun to adopt the Transformer to combine or replace the
widely used ResNet as their new backbone network. As the Transformer captures the long …

Visible-infrared person re-identification (VI-ReID) is a challenging cross-modality image
retrieval task. Compared to visible modality person re-identification that handles only the …

Event cameras, unlike traditional frame-based cameras, excel in detecting and reporting
changes in light intensity on a per-pixel basis. This unique technology offers numerous …

The neuromorphic event cameras can efficiently sense the latent geometric structures and
motion clues of a scene by generating asynchronous and sparse event signals. Due to the …

Siamese network based trackers develop rapidly in the field of visual object tracking in
recent years. The majority of Siamese network based trackers now in use treat each channel …

Bio-inspired event cameras have been considered effective alternatives to traditional frame-
based cameras for stereo depth estimation, especially in challenging conditions such as low …

In long-term video object tracking (VOT) tasks, most long-term trackers are modified from
short-term trackers, which contain more and more machine learning modules to improve …

Visual tracking is a task of localizing a target unceasingly in a video with an initial target
state at the first frame. The limited target information makes this problem an extremely …