In this paper, we present a systematic framework for recognizing realistic actions from videos “in the wild.” Such unconstrained videos are abundant in personal collections as...
Emerging languages are often source-to-source compiled to mainstream ones, which offer standardized, fine-tuned implementations of non-functional concerns (NFCs)—including pers...
In this paper, we present a systematic framework for re-cognizing realistic actions from videos “in the wild.” Such unconstrained videos are abundant in personal collections as...
Jingen Liu (University of Central Florida), Jiebo ...
In this paper, we present CONTRAlign, an extensible and fully automatic framework for parameter learning and protein pairwise sequence alignment using pair conditional random field...
In this paper, we present a scene detection framework on continuously recorded videos. Conventional temporal scene segmentation methods work for the videos composed of discrete sh...