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Angela Yao
Researcher at National University of Singapore
Publications - 107
Citations - 3644
Angela Yao is an academic researcher from National University of Singapore. The author has contributed to research in topics: Computer science & Pose. The author has an hindex of 26, co-authored 86 publications receiving 2845 citations. Previous affiliations of Angela Yao include ETH Zurich & University of Bonn.
Papers
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Journal ArticleDOI
Hough Forests for Object Detection, Tracking, and Action Recognition
TL;DR: Hough forests can be regarded as task-adapted codebooks of local appearance that allow fast supervised training and fast matching at test time that improve the performance of the generalized Hough transform for object detection on a categorical level and extend to new domains such as object tracking and action recognition.
Proceedings ArticleDOI
A Hough transform-based voting framework for action recognition
TL;DR: It is demonstrated that Hough-voting can achieve state-of-the-art performance on several datasets covering a wide range of action-recognition scenarios.
Proceedings ArticleDOI
A Two-Streamed Network for Estimating Fine-Scaled Depth Maps from Single RGB Images
Jun Li,Reinhard Klein,Angela Yao +2 more
TL;DR: In this article, a fast-to-train two-streamed CNN is proposed to predict depth and depth gradients, which are then fused together into an accurate and detailed depth map.
Proceedings ArticleDOI
Does Human Action Recognition Benefit from Pose Estimation
TL;DR: Comparing pose-based, appearance-based and combined pose and appearance features for action recognition in a home-monitoring scenario shows that posebased features outperform low-level appearance features, even when heavily corrupted by noise, suggesting that pose estimation is beneficial for the action recognition task.
Proceedings ArticleDOI
Dense 3D Regression for Hand Pose Estimation
TL;DR: Zhang et al. as discussed by the authors decompose the pose parameters into a set of per-pixel estimations, i.e., 2D heat maps, 3D heatmaps and unit 3D directional vector fields.