456 citations · 1.1k across the 26 of their papers we have counts for
6 papers · 1 filter
DenseNet for Dense Flow
Yi Zhu, Shawn Newsam
Classical approaches for estimating optical flow have achieved rapid progress in the last decade. However, most of them are too slow to be applied in real-time video analysis. Due…
Large-Scale Mapping of Human Activity using Geo-Tagged Videos
Yi Zhu, Sen Liu, Shawn Newsam
This paper is the first work to perform spatio-temporal mapping of human activity using the visual content of geo-tagged videos. We utilize a recent deep-learning based video analy…
UC Merced Submission to the ActivityNet Challenge 2016
Yi Zhu, Shawn Newsam, Zaikun Xu
This notebook paper describes our system for the untrimmed classification task in the ActivityNet challenge 2016. We investigate multiple state-of-the-art approaches for action rec…
Hidden Two-Stream Convolutional Networks for Action Recognition
Yi Zhu, Zhenzhong Lan, Shawn Newsam +1
Analyzing videos of human actions involves understanding the temporal relationships among video frames. State-of-the-art action recognition approaches rely on traditional optical f…
Guided Optical Flow Learning
Yi Zhu, Zhenzhong Lan, Shawn Newsam +1
We study the unsupervised learning of CNNs for optical flow estimation using proxy ground truth data. Supervised CNNs, due to their immense learning capacity, have shown superior p…
Deep Local Video Feature for Action Recognition
Zhenzhong Lan, Yi Zhu, Alexander G. Hauptmann
We investigate the problem of representing an entire video using CNN features for human action recognition. Currently, limited by GPU memory, we have not been able to feed a whole…