Deep Learning Methods for Efficient Large Scale Video Labeling
arXiv:1706.04572v115 citations
AI Analysis
This work addresses video understanding for applications like content analysis, but it is incremental as it builds on existing methods without introducing new paradigms.
The authors tackled the problem of large-scale video labeling by developing an ensemble model that ranked 5th in the Google Cloud and YouTube-8M Video Understanding Challenge.
We present a solution to "Google Cloud and YouTube-8M Video Understanding Challenge" that ranked 5th place. The proposed model is an ensemble of three model families, two frame level and one video level. The training was performed on augmented dataset, with cross validation.