Temporal Tessellation: A Unified Approach for Video Analysis

Dotan Kaufman, Gil Levi, Tal Hassner, Lior Wolf

نتاج البحث: فصل من :كتاب / تقرير / مؤتمرمنشور من مؤتمرمراجعة النظراء


We present a general approach to video understanding, inspired by semantic transfer techniques that have been successfully used for 2D image analysis. Our method considers a video to be a 1D sequence of clips, each one associated with its own semantics. The nature of these semantics - natural language captions or other labels - depends on the task at hand. A test video is processed by forming correspondences between its clips and the clips of reference videos with known semantics, following which, reference semantics can be transferred to the test video. We describe two matching methods, both designed to ensure that (a) reference clips appear similar to test clips and (b), taken together, the semantics of the selected reference clips is consistent and maintains temporal coherence. We use our method for video captioning on the LSMDC'16 benchmark, video summarization on the SumMe and TV-Sum benchmarks, Temporal Action Detection on the Thumos2014 benchmark, and sound prediction on the Greatest Hits benchmark. Our method not only surpasses the state of the art, in four out of five benchmarks, but importantly, it is the only single method we know of that was successfully applied to such a diverse range of tasks.

اللغة الأصليةالإنجليزيّة
عنوان منشور المضيفProceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017
ناشرInstitute of Electrical and Electronics Engineers Inc.
عدد الصفحات11
رقم المعيار الدولي للكتب (الإلكتروني)9781538610329
المعرِّفات الرقمية للأشياء
حالة النشرنُشِر - 22 ديسمبر 2017
الحدث16th IEEE International Conference on Computer Vision, ICCV 2017 - Venice, إيطاليا
المدة: ٢٢ أكتوبر ٢٠١٧٢٩ أكتوبر ٢٠١٧

سلسلة المنشورات

الاسمProceedings of the IEEE International Conference on Computer Vision
مستوى الصوت2017-October
رقم المعيار الدولي للدوريات (المطبوع)1550-5499


!!Conference16th IEEE International Conference on Computer Vision, ICCV 2017

ملاحظة ببليوغرافية

Publisher Copyright:
© 2017 IEEE.


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