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20172023
most citedMulti-View Spectral Clustering with High-Order Optimal Neighborhood Laplacian Matrix

9 citations · 38 across the 13 of their papers we have counts for

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6 papers · 1 filter

cs.CV20216 cited

Video Abnormal Event Detection by Learning to Complete Visual Cloze Tests

Siqi Wang, Guang Yu, Zhiping Cai +3

Although deep neural networks (DNNs) enable great progress in video abnormal event detection (VAD), existing solutions typically suffer from two issues: (1) The localization of vid…

cs.CV2021

Multi-view Deep One-class Classification: A Systematic Exploration

Siqi Wang, Jiyuan Liu, Guang Yu +5

One-class classification (OCC), which models one single positive class and distinguishes it from the negative class, has been a long-standing topic with pivotal application to real…

cs.CV2021

Deep Distribution-preserving Incomplete Clustering with Optimal Transport

Mingjie Luo, Siwei Wang, Xinwang Liu +5

Clustering is a fundamental task in the computer vision and machine learning community. Although various methods have been proposed, the performance of existing approaches drops dr…

cs.CV2020

Embedded Deep Bilinear Interactive Information and Selective Fusion for Multi-view Learning

Jinglin Xu, Wenbin Li, Jiantao Shen +5

As a concrete application of multi-view learning, multi-view classification improves the traditional classification methods significantly by integrating various views optimally. Al…

cs.CV2018

Deep Learning for Generic Object Detection: A Survey

Li Liu, Wanli Ouyang, Xiaogang Wang +4

Object detection, one of the most fundamental and challenging problems in computer vision, seeks to locate object instances from a large number of predefined categories in natural…

cs.CV20179 cited

DeepKSPD: Learning Kernel-matrix-based SPD Representation for Fine-grained Image Recognition

Melih Engin, Lei Wang, Luping Zhou +1

Being symmetric positive-definite (SPD), covariance matrix has traditionally been used to represent a set of local descriptors in visual recognition. Recent study shows that kernel…