Learning latent temporal structure for complex event detection

Abstract

In this paper, we tackle the problem of understanding the temporal structure of complex events in highly varying videos obtained from the Internet. Towards this goal, we utilize a conditional model trained in a max-margin framework that is able to automatically discover discriminative and interesting segments of video, while simultaneously achieving… (More)
DOI: 10.1109/CVPR.2012.6247808

8 Figures and Tables

Topics

Statistics

0204060802012201320142015201620172018
Citations per Year

373 Citations

Semantic Scholar estimates that this publication has 373 citations based on the available data.

See our FAQ for additional information.

  • Presentations referencing similar topics