Recent transformer-based offline video instance segmentation (VIS) approaches achieve encouraging results and significantly outperform online approaches. However, their reliance on the whole immense computational complexity caused by full Spatio-temporal attention limit them in real-life applications such as processing lengthy videos. In this paper, we propose a single-stage efficient VIS frame...

In this work, we present SeqFormer for video instance segmentation. follows the principle of vision transformer that models relationships among frames. Nevertheless, observe a stand-alone query suffices capturing time sequence instances in video, but attention mechanisms shall be done with each frame independently. To achieve this, locates an and aggregates temporal information to learn powerfu...

Shot boundary detection is the process of segmenting a video into basic units known as shots by discovering transition frames between shots. Researches have been conducted to accurately detect shot boundaries. However, acceleration with higher accuracy needs improvement. A new method was introduced in this paper find out boundaries abrupt high and lower computational cost. The proposed consists...

Instance segmentation is a challenging task aiming at classifying and segmenting all object instances of specific classes. While two-stage box-based methods achieve top performances in the image domain, they cannot easily extend their superiority into video domain. This because usually deal with features or images cropped from detected bounding boxes without alignment, failing to capture pixel-...

In this paper we investigate the applicability of the MultiAgent paradigm to the realization of a distributed software system suitably designed for Mpeg video segmentation. This task is performed by combining at different levels video and audio information. We present a general discussion of the characteristics of Multi Agents showing how they satisfy the needs of the quoted video segmentation ...