Zhongqian Sun

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Occlusions are challenging issue for robust visual tracking. In this paper, motivated by the fact that a tracked object is usually embedded into context that provides useful information for estimating the target, we propose a novel tracking algorithm named Tracking with Context Prediction (TCP). The context here includes the neighboring objects and specific(More)
Traditional mean shift method has the limitation that could not effectively adjust kernel bandwidth to represent object accurately. To address this problem, in this paper, we propose a novel contour tracking algorithm using a determined binary level set model (DBLSM) based on mean shift procedure. In contrast with other previous work, the computational(More)
We propose a novel object tracking algorithm based on modeling the target appearance in a joint space. In contrast with traditional histogram-based trackers which discard all spatial information, the joint space takes both the photometric and spatial information into account. Within this joint space, the target is modeled in a Gaussian mixtures manner where(More)
We propose a novel framework based on neural networks to identify the sentiment of opinion targets in a comment/review. Our framework adopts multiple-attention mechanism to capture sentiment features separated by a long distance, so that it is more robust against irrelevant information. The results of multiple attentions are non-linearly combined with a(More)
Sentiment analysis in social media has attracted significant attention. Although researchers have proposed many methods, a single method is hard to meet requirement in industrial applications. In this paper, based on massive data of Tencent and industrial practice, we present a multilayered analysis system (MAS) on social media. The system is composed of(More)
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