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Hongye Liu and Xiai Chen
Person re-identification aims to identify the same pedestrians captured by various cameras from different viewpoints in multiple scenarios. Occlusion is the toughest problem for practical applications. In video-based ReID tasks, motion information can be...
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Shengyu Pei and Xiaoping Fan
Existing person re-recognition (Re-ID) methods usually suffer from poor generalization capability and over-fitting problems caused by insufficient training samples. We find that high-level attributes, semantic information, and part-based local informatio...
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Shengbo Chen, Hongchang Zhang and Zhou Lei
Person re-identification (ReID) plays a significant role in video surveillance analysis. In the real world, due to illumination, occlusion, and deformation, pedestrian features extraction is the key to person ReID. Considering the shortcomings of existin...
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Zhou Lei, Kangkang Yang, Kai Jiang and Shengbo Chen
Person re-Identification(Re-ID) based on deep convolutional neural networks (CNNs) achieves remarkable success with its fast speed. However, prevailing Re-ID models are usually built upon backbones that manually design for classification. In order to aut...
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Xing Fan, Wei Jiang, Hao Luo, Weijie Mao and Hongyan Yu
Traditional Person Re-identification (ReID) methods mainly focus on cross-camera scenarios, while identifying a person in the same video/camera from adjacent subsequent frames is also an important question, for example, in human tracking and pose trackin...
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Shaojun Wu and Ling Gao
In person re-identification, extracting image features is an important step when retrieving pedestrian images. Most of the current methods only extract global features or local features of pedestrian images. Some inconspicuous details are easily ignored ...
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Hua Gao, Shengyong Chen and Zhaosheng Zhang
Person re-identification is a typical computer vision problem which aims at matching pedestrians across disjoint camera views. It is challenging due to the misalignment of body parts caused by pose variations, background clutter, detection errors, camera...
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