Video Processing and Understanding Lab
Universidad Autónoma de Madrid, Escuela Politécnica Superior

TEC2017-88169-R MobiNetVideo (2018-2020-2021)
Visual Analysis for Practical Deployment of Cooperative Mobile Camera Networks

MobiNetVideo_logo
Supported by the
Ministerio de Economía, Industria y Competividad
of the Spanish Goverment
Public Resources: Content Sets and Software

Content Sets

  • P365LLds: A Places365 Lifelogging version Dataset. (available on-demand; to be available on-line soon)
    The task of scene recognition has been classically evaluated using still images representing scenes. In the context of the MobiNetVideo project, we have created a new dataset that extrapolates Places365's classes to lifelogging/egocentric videos. The dataset is made up of 450 videos recorded with smartphones, go-pro and handheld cameras. Videos have been obtained by downloading YouTube videos licensed as Creative Commons. For each scene class in Places365, we include between one (90% of the classes) and four videos. The average length of the videos is 638 frames (around twenty-one seconds) and the median length is 600 frames per video (around twenty seconds). In overall, the dataset is approximately 34.1 GB large.

  • USSds: A Unified Semantic Segmentation Dataset (available on-demand; to be available on-line soon)
    There is a large variety of semantic datasets. However, not all of them have the same semantic classes, and the appearance of shared classes substantially differ. The USSds represents a data integration effort to create a unified semantic dataset which—by enlarging the number of classes and the diversity of the shared classes, aims to provide a more generic benchmark for training and evaluation. The merged datasets have been relabelled to a common set of 293 semantic labels distributed into a total of 145,555 training images and 7,614 validation images. The datasets agglutinated to compose the USSds dataset are: COCO-Stuff Dataset, Cityscapes Dataset, ADE20K Dataset, TASKONOMY Dataset, and Mapillary Dataset.

Software

Last update 27/02/2022
Universidad Autónoma de Madrid, Escuela Politécnica Superior
Video Processing and Understanding Lab