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Article
MEAN: An attention-based approach for 3D mesh shape classification
3D shape processing is a fundamental computer application. Specifically, 3D mesh could provide a natural and detailed way for object representation. However, due to its non-uniform and irregular data structure...
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Article
Hybrid feature constraint with clustering for unsupervised person re-identification
Unsupervised person re-identification (Re-ID) has better scalability and usability in real-world deployments due to the lack of annotations, which is more challenging than supervised methods. State-of-the-art ...
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Article
DRDDN: dense residual and dilated dehazing network
Recently, deep convolutional neural networks (CNNs) have made great achievements in image restoration. However, there exists a large space to improve the performance of CNN-based dehazing model. In this paper,...
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Article
A novel privacy-preserving outsourcing computation scheme for Canny edge detection
With the advancement of cloud computing technology, cloud servers are utilized to process large-scale data, especially multimedia data. However, concerns about leakage of private information prevent cloud comp...
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Article
A multi-phase blending method with incremental intensity for training detection networks
Object detection is an important topic for visual data processing in the visual computing area. Although a number of approaches have been studied, it still remains a challenge. There is a suitable way to promo...
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Article
Open AccessWeight asynchronous update: Improving the diversity of filters in a deep convolutional network
Deep convolutional networks have obtained remarkable achievements on various visual tasks due to their strong ability to learn a variety of features. A well-trained deep convolutional network can be compressed...
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Article
DRCDN: learning deep residual convolutional dehazing networks
Single image dehazing, which is the process of removing haze from a single input image, is an important task in computer vision. This task is extremely challenging because it is massively ill-posed. In this pa...
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Article
Part-based visual tracking with spatially regularized correlation filters
Discriminative Correlation Filters (DCFs) have demonstrated excellent performance in visual object tracking. These methods utilize a periodic assumption of the training samples to efficiently learn a classifie...
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Article
Joint learning of image detail and transmission map for single image dehazing
Single image haze removal is an important task in computer vision. However, haze removal is an extremely challenging problem due to its massively ill-posed, which is that at each pixel we must estimate the tra...
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Article
Performance-based control interfaces using mixture of factor analyzers
This paper introduces an approach to performance animation that employs a small number of inertial measurement sensors to create an easy-to-use system for an interactive control of a full-body human character....