Pasts: Toward Effective Distilling Transformer For Panoramic Semantic Segmentation

in recent years, video has dominated internet traffic and has become one of the major media formats. Besides its consumption by humans, videos are now often consumed by machines for analysis tasks such as object detection, segmentation, tracking, etc. Thus, efficient video coding for machines (VCM) becomes an important topic in academia and industry. Datasets are essential in the evaluation of a variety of coding tools for VCM. However, most of the publicly available datasets are only for academic usage, which prohibits their usage for many participants in the field of VCM study. in this paper, an open dataset with permissive license terms will be introduced. This dataset has been accepted by MPEG-VCM group as a test dataset. It is based on a larger video dataset, of which annotations for a subset of images are used to evaluate the performance of object detection and instance segmentation tasks. in addition, annotations for object tracking for a subset of videos are provided. The characteristics of the dataset and details of the annotations will be described. Evaluation results for multiple machine vision tasks will be presented to demonstrate the usage of the dataset.