Paper Abstract The massive growth of sports videos has resulted in a need for automatic generation of sports highlights that are comparable in quality to the hand-edited highlights produced by broadcasters such as ESPN. Unlike previous works that mostly use audio-visual cues derived from the video, we propose an approach that additionally leverages contextual cues […]
Paper / Citation 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 a “dog”, without employing any pre-trained object detectors. We formulate […]
K. Kim, I. Essa, and G. Abowd (2006) “Interactive mosaic generation for video navigation.” in Proceedings of the 14th annual ACM international conference on Multimedia, pages 655-658, 2006. [Project Page | DOI | PDF] Abstract Navigation through large multimedia collections that include videos and images still remains cumbersome. In this paper, we introduce a novel method […]