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Machine learning techniques, namely convolutional neural networks (CNN) and regression forests, have recently shown great promise in performing 6-DoF localization of monocular images. However, in most cases image-sequences, rather only single images, are readily available. To this extent, none of the proposed learning-based approaches exploit the valuable constraint of temporal smoothness, often leading...
Making virtual human's actions more natural and more approaching to reality is helpful for enhancing intelligibility of synthesized Chinese sign language (CSL). Usually action with prosody looks more vivid and prosody means that same word has discriminating style according to different context. The problem here is how to find and indicate the context. As formal description for CSL, CSLML provides...
Matching vehicles subject to both large pose transformations and extreme illumination variations remains a technically challenging problem in computer vision. In this paper, we develop a new and robust framework toward matching and recognizing vehicles with both highly varying poses and drastically changing illumination conditions. By effectively estimating both pose and illumination conditions, we...
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