4 accepted papers
Modern face alignment methods have become quite accurate at predicting the locations of facial landmarks, but they do not typically estimate the uncertainty of their predicted locations nor predict whether landmarks are visible. In this paper, we present a novel framework for jointly predicting land…
We present a multi-stream bi-directional recurrent neural network for fine-grained action detection. Recently, two-stream convolutional neural networks (CNNs) trained on stacked optical flow and image frames have been successful for action recognition in videos. Our system uses a tracking algorithm…
In this work we propose a method for simultaneously learning features and a corresponding similarity metric for person re-identification. We present a deep convolution architecture with layers specially designed to address the problem of re-identification. Given a pair of images as input, our networ…
We present a real-time system for 3D head pose estimation and facial landmark localization using a commodity depth sensor. We introduce a novel triangular surface patch (TSP) descriptor, which encodes the shape of the 3D surface of the face within a triangular area. The proposed descriptor is viewpo…