Multi-object Tracking (MOT) is very important in human surveillance, sports analytics,
autonomous driving, and cooperative robots. Current MOT methods do not perform well in …

Transformer-based methods have demonstrated superior performance for monocular 3D
object detection recently, which aims at predicting 3D attributes from a single 2D image …

Geometry plays a significant role in monocular 3D object detection. It can be used to
estimate object depth by using the perspective projection between object's physical size and …

Monocular 3D detectors achieve remarkable performance on cars and smaller objects.
However their performance drops on larger objects leading to fatal accidents. Some attribute …

In the wake of developments in consumer electronics, electric vehicles are gradually
becoming representative carriers of next-generation consumer electronics. Electric vehicles …

Monocular 3D object detection plays a pivotal role in autonomous driving, presenting a
formidable challenge by requiring the precise localization of 3D objects within a single …

This paper proposes a method for enhancing vehicle monocular three-dimensional
perception using vehicle re-identification (Re-ID) and collaborative vehicle infrastructure …

The field of autonomous vehicles (AVs) predominantly leverages multi-modal integration of
LiDAR and camera data to achieve better performance compared to using a single modality …

Monocular 3D object detection has attracted great attention due to simplicity and low cost.
However, object location recovery in the 3D space from a monocular image is challenging …

Recently, transformer-based methods have shown exceptional performance in monocular
3D object detection, which can predict 3D attributes from a single 2D image. These methods …