Vision systems that see and reason about the compositional nature of visual scenes are
fundamental to understanding our world. The complex relations between objects and their …

Unmanned aerial vehicle (UAV)-based visual object tracking has enabled a wide range of
applications and attracted increasing attention in the field of artificial intelligence (AI) …

Metaverse and intelligent transportation system (ITS) are disruptive technologies that have
the potential to transform the current transportation system by decreasing traffic accidents …

Enhancing images in low-light scenes is a challenging but widely concerned task in the
computer vision. The mainstream learning-based methods mainly acquire the enhanced …

Object detection at night is a challenging problem due to the absence of night image
annotations. Despite several domain adaptation methods, achieving high-precision results …

Black-box unsupervised domain adaptation (UDA) learns with source predictions of target
data without accessing either source data or source models during training, and it has clear …

In recent years, the field of unmanned aerial vehicle (UAV) tracking has grown rapidly,
finding numerous applications across various industries. While the discriminative correlation …

In this paper we make the first attempt at achieving the cross-modal (ie image-to-events)
adaptation for event-based object recognition without accessing any labeled source image …

Satellite videos capture the dynamic changes in a large observed sense, which provides an
opportunity to track the object trajectories. However, existing multiple object tracking (MOT) …

The perception of drones, also known as Unmanned Aerial Vehicles (UAVs), particularly in
infrared videos, is crucial for effective anti-UAV tasks. However, existing datasets for UAV …