Moving object segmentation (MOS) is the process of identifying dynamic objects from video
frames, such as moving vehicles or pedestrians, while discarding the background. It plays …

Advances in moving object detection have been driven by the active application of deep
learning methods. However, many existing models render superior detection accuracy at the …

Moving Object Segmentation (MOS) is a challenging problem in computer vision, particularly
in scenarios with dynamic backgrounds, abrupt lighting changes, shadows, camouflage, and …

Recently, it's been a breeze to snap photos of high quality and good size, thanks to the
widespread availability of low-cost but technologically advanced photo-capturing devices. A …

Moving object detection is still a challenging task in complex scenes. The existing methods
based on deep learning mainly use U-Nets and have achieved amazing results. However …

Video prediction is an essential vision task due to its wide applications in real-world
scenarios. However, it is indeed challenging due to the inherent uncertainty and complex …

Deep learning methods have been actively applied in moving object detection and achieved
great performance. However, many existing models render superior detection accuracy at …

Background subtraction is a challenging and fundamental task in computer vision, which
aims at segmenting moving objects from the background. Recently, the attention mechanism …

Compressed sensing is an effective solution for signal acquisition and signal reconstruction
at a much lower rate than the Nyquist rate. Traditional methods, such as orthogonal …

Moving target detection is one of the most basic tasks in computer vision. In conventional
wisdom, the problem is solved by iterative optimization under either Matrix Decomposition …