no code implementations • ECCV 2020 • Lezi Wang, Dong Liu, Rohit Puri, Dimitris N. Metaxas
We introduce a novel ranking network that utilizes the Co-Attention between movies and trailers as guidance to generate the training pairs, where the moments highly corrected with trailers are expected to be scored higher than the uncorrelated moments.
no code implementations • 19 Aug 2020 • Lezi Wang, Dong Liu, Rohit Puri, Dimitris N. Metaxas
A movie's key moments stand out of the screenplay to grab an audience's attention and make movie browsing efficient.
no code implementations • 25 Jul 2019 • Dong Liu, Rohit Puri, Nagendra Kamath, Subhabrata Bhattachary
In this work, we propose to model the image composition information as the mutual dependency of its local regions, and design a novel architecture to leverage such information to boost the performance of aesthetics assessment.
no code implementations • 14 Dec 2018 • Naji Khosravan, Shervin Ardeshir, Rohit Puri
To judge whether audio and video signals of a multimedia presentation are synchronized, we as humans often pay close attention to discriminative spatio-temporal blocks of the video (e. g. synchronizing the lip movement with the utterance of words, or the sound of a bouncing ball at the moment it hits the ground).