Conventional neural networks have been demonstrated to be a powerful framework for
background subtraction in video acquired by static cameras. Indeed, the well-known Self …

During about 30 years, a lot of research teams have worked on the big challenge of
detection of moving objects in various challenging environments. First applications concern …

Background subtraction, although being a very well-established field, has required
significant research efforts to tackle unsolved challenges and to accelerate the progress …

Moving object detection is a fundamental step in various computer vision applications.
Robust principal component analysis (RPCA)-based methods have often been employed for …

Background estimation and foreground segmentation are important steps in many high-level
vision tasks. Many existing methods estimate background as a low-rank component and …

To address the challenges of change detection in the wild, we present a novel background
subtraction algorithm based on parallel vision and Bayesian generative adversarial …

A new method is proposed for removing text from natural images. The challenge is to first
accurately localize text on the stroke-level and then replace it with a visually plausible …

Moving object segmentation (MOS), aiming at segmenting moving objects from video
frames, is an important and challenging task in computer vision and with various …

Background subtraction is an effective method of choice when it comes to detection of
moving objects in videos and has been recognized as a breakthrough for the wide range of …

For image classification, convolutional neural networks (CNNs) have the advantage of being
able to convolve directly with image pixels and extract image features from image pixels …