Paper in ECCV Workshop 2012: “Weakly Supervised Learning of Object Segmentations from Web-Scale Videos”

Citation

  • G. Hartmann, M. Grundmann, Judy Hoffman, D. Tsai, V. Kwatra, Omid Madani, S. Vijayanarasimhan, Irfan Essa, J. Rehg, and R. Sukthankar (2012), “Weakly Supervised Learning of Object Segmentations from Web-Scale Videos,” in Proceedings of ECCV 2012 Workshop on Web-scale Vision and Social Media, 2012. [PDF] [DOI] [BIBTEX]
    @InProceedings{ 2012-Hartmann-WSLOSFWV,
    author  = {Glenn Hartmann and Matthias Grundmann and Judy
    Hoffman and David Tsai and Vivek Kwatra and Omid
    Madani and Sudheendra Vijayanarasimhan and Irfan
    Essa and James Rehg and Rahul Sukthankar},
    booktitle  = {Proceedings of ECCV 2012 Workshop on Web-scale
    Vision and Social Media},
    doi = {10.1007/978-3-642-33863-2_20},
    pdf = {http://www.cs.cmu.edu/~rahuls/pub/eccv2012wk-cp-rahuls.pdf},
    title = {Weakly Supervised Learning of Object Segmentations
    from Web-Scale Videos},
    year = {2012}
    }

Abstract

We propose to learn pixel-level segmentations of objects from weakly labeled (tagged) internet videos. Espe cially, given a large collection of raw YouTube content, along with potentially noisy tags, our goal is to automatically generate spatiotemporal masks for each object, such as dog”, without employing any pre-trained object detectors. We formulate this problem as learning weakly supervised classi ers for a set of independent spatio-temporal segments. The object seeds obtained using segment-level classi ers are further re ned using graphcuts to generate high-precision object masks. Our results, obtained by training on a dataset of 20,000 YouTube videos weakly tagged into 15 classes, demonstrate automatic extraction of pixel-level object masks. Evaluated against a ground-truthed subset of 50,000 frames with pixel-level annotations, we con rm that our proposed methods can learn good object masks just by watching YouTube.
Presented at: ECCV 2012 Workshop on Web-scale Vision and Social Media, 2012, October 7-12, 2012, in Florence, ITALY.
Awarded the BEST PAPER AWARD!

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.