Towards in-store multi-person tracking using head detection and track heatmaps

1 code implementation • 16 May 2020 • Aibek Musaev, Jiangping Wang, Liang Zhu, Cheng Li, Yi Chen, Jialin Liu, Wanqi Zhang, Juan Mei, De Wang

In addition, we describe an illustrative example of the use of this dataset for tracking participants based on a head tracking model in an effort to minimize errors due to occlusion.

Head Detection

Argoverse: 3D Tracking and Forecasting with Rich Maps

3 code implementations • CVPR 2019 • Ming-Fang Chang, John Lambert, Patsorn Sangkloy, Jagjeet Singh, Slawomir Bak, Andrew Hartnett, De Wang, Peter Carr, Simon Lucey, Deva Ramanan, James Hays

In our baseline experiments, we illustrate how detailed map information such as lane direction, driveable area, and ground height improves the accuracy of 3D object tracking and motion forecasting.

3D Object Tracking Autonomous Vehicles +3

Scalable and accurate deep learning for electronic health records

no code implementations • 24 Jan 2018 • Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Peter J. Liu, Xiaobing Liu, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Gavin E. Duggan, Gerardo Flores, Michaela Hardt, Jamie Irvine, Quoc Le, Kurt Litsch, Jake Marcus, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael Howell, Claire Cui, Greg Corrado, Jeff Dean

Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality.

Inexact Proximal Gradient Methods for Non-convex and Non-smooth Optimization

no code implementations • 18 Dec 2016 • Bin Gu, De Wang, Zhouyuan Huo, Heng Huang

The theoretical results show that our inexact proximal gradient algorithms can have the same convergence rates as the ones of exact proximal gradient algorithms in the non-convex setting.

BIG-bench Machine Learning