video-panoptic-segmentation-models

Video Panoptic Segmentation Network

VPSNet: A Model for Video Panoptic Segmentation If you are interested in computer vision and machine learning, you may have heard of VPSNet, which stands for Video Panoptic Segmentation Network. This is a model that has been developed for video panoptic segmentation, which is a process of identifying and classifying all objects in an image or video scene. The model is based on UPSNet, which is a method for image panoptic segmentation, and it takes an additional frame as a reference to correlate

ViP-DeepLab

Introduction to ViP-DeepLab ViP-DeepLab is a model used for depth-aware video panoptic segmentation. This model was created by adding a depth prediction head and a next-frame instance branch to the already existing Panoptic-DeepLab model. By doing so, ViP-DeepLab is able to perform video panoptic segmentation and monocular depth estimation simultaneously. What is Depth-Aware Video Panoptic Segmentation? Video panoptic segmentation is a process that includes segmenting objects and backgrounds

1 / 1